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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Поддерживает ввод нескольких поисковых фраз (по одной на строку). При поиске обеспечивает поддержку морфологии русского и английского языка
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Применить Всего найдено 43. Отображено 43.
31-03-2015 дата публикации

System and method for composite distance metric leveraging multiple expert judgments

Номер: US0008996443B2
Автор: Shahram Ebadollahi, Jimeng Sun, Fei Wang, EBADOLLAHI SHAHRAM, SUN JIMENG, WANG FEI
Принадлежит: International Business Machines Corporation, IBM, INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

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Номер записи: 1
19-10-2010 дата публикации

Method and apparatus for automatic multimedia narrative enrichment

Номер: US0007818329B2
Автор: Murray S. Campbell, Shahram Ebadollahi, Matthew L. Hill, Brian Michael Landry, Chung-Sheng Li, Apostol Ivanov Natsev, Milind R. Naphade, John R. Smith, Jelena Tesic, Lexing Xie, CAMPBELL MURRAY S, EBADOLLAHI SHAHRAM, HILL MATTHEW L, LANDRY BRIAN MICHAEL, LI CHUNG-SHENG, NATSEV APOSTOL IVANOV, NAPHADE MILIND R, SMITH JOHN R, TESIC JELENA, XIE LEXING, CAMPBELL MURRAY S., HILL MATTHEW L., NAPHADE MILIND R., SMITH JOHN R.
Принадлежит: International Business Machines Corporation, IBM, INTERNATIONAL BUSINESS MACHINES CORPORATION

A method and apparatus is disclosed that receives an input narrative in a particular media format, and produces therefrom a multimedia enriched version of the input narrative. In one embodiment, a method is provided for enriching an input narrative with multimedia content, wherein the method includes the step of selectively segmenting the input narrative to form queries pertaining to different portions or elements of the input narrative. The method further comprises retrieving multimedia artifacts from one or more multimedia repositories, wherein each retrieved multimedia artifact is associated with one of the queries, and selecting a subset of the retrieved multimedia artifacts, wherein the subset includes artifacts comprising different types of multimedia content. The input narrative is then combined with respective multimedia artifacts of the subset, in order to provide an enriched and enhanced narrative.

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Номер записи: 2
16-02-2012 дата публикации

SYSTEM AND METHOD FOR PREDICTING LONG-TERM PATIENT OUTCOME

Номер: US20120041772A1
Автор: Shahram Ebadollahi, Jianying Hu, Robert K. Sorrentino, Daby M. Sow, Jimeng Sun, EBADOLLAHI SHAHRAM, HU JIANYING, SORRENTINO ROBERT K, SOW DABY M, SUN JIMENG, SORRENTINO ROBERT K., SOW DABY M.
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for predicting patient prognosis includes a similarity module configured in program storage media to provide a similarity function for a data source and compute similarity scores for pairs of patients. An alignment module is configured to align a query patient to a best anchor timestamp of a similar patient or patients so that a comparison between the query patient and at least one similar patient is provided. A prediction module is configured to predict a long-term outcome measure of the query patient based on data from the at least one similar patient.

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Номер записи: 3
20-06-2019 дата публикации

PERSONALIZED INTERVENTION BASED ON MACHINE LEARNING OF BEHAVIOR CHANGE STATES

Номер: US20190189025A1
Автор: Marie Angelopoulos, Shahram Ebadollahi, Stewart T. Sill, Michal Rosen-Zvi, Ching-Hua Chen, James V. Codella, Si Sun, ANGELOPOULOS MARIE, EBADOLLAHI SHAHRAM, SILL STEWART T, ROSEN-ZVI MICHAL, CHEN CHING-HUA, CODELLA JAMES V, SUN SI, Angelopoulos, Marie, Ebadollahi, Shahram, Sill, Stewart T., Rosen-Zvi, Michal, Chen, Ching-Hua, Codella, James V., Sun, Si
Принадлежит:

A system provides an intervention for a user and comprises at least one processor. The system monitors behavior and context of a user to generate a behavior history. One or more models are utilized to determine an intervention for the user to induce a behavior modification, wherein the one or more models map interventions to user context and behavior and utilize the behavior history to determine an effective intervention for the user. The intervention is provided to the user and feedback is received in response to the intervention. The one or more models are updated based on the feedback. Embodiments of the present invention further include a method and computer program product for providing an intervention to a user in substantially the same manner described above. 1. A method of providing an intervention for a user comprising:monitoring behavior and context of a user, via a processor, to generate a behavior history;utilizing one or more models, via a processor, to determine an intervention for the user to induce a behavior modification, wherein the one or more models map interventions to user context and behavior and utilize the behavior history to determine an effective intervention for the user;providing the intervention to the user, via a processor, and receiving feedback in response to the intervention; andupdating the one or more models, via a processor, based on the feedback.2. The method of claim 1 , wherein the determined intervention includes information relevant to inducing the behavior modification claim 1 , and comprises one of a health and wellness intervention and a lifestyle intervention.3. The method of claim 1 , wherein the one or more models include a user behavior profile with a plurality of dimensions claim 1 , wherein the user behavior profile is associated with a corresponding behavior target and user context claim 1 , and the plurality of dimensions includes elements of behavior and purposes of interventions.4. The method of claim 3 , ...

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Номер записи: 4
24-10-2013 дата публикации

COMBINING KNOWLEDGE AND DATA DRIVEN INSIGHTS FOR IDENTIFYING RISK FACTORS IN HEALTHCARE

Номер: US20130282390A1
Автор: Shahram Ebadollahi, Jianying Hu, Dijun Luo, Marianthi Markatou, Jimeng Sun, Fei Wang
Принадлежит: International Business Machines Corporation

Systems and methods for risk factor identification include identifying a first set of risk factors from personal data. A second set of risk factors is identified from at least one of a user input and a knowledge source. The first set is combined with the second set, using a processor, by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest. 1. A computer implemented method for risk factor identification , comprising:identifying a first set of risk factors from personal data;identifying a second set of risk factors from at least one of a user input and a knowledge source; andcombining, using a processor, the first set with the second set by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest.2. The computer implemented method as recited in claim 1 , wherein combining includes modeling the first set and the second set as an objective function.3. The computer implemented method as recited in claim 2 , wherein the objective function includes a regression model as a reconstruction error representing how accurate the combined list of risk factors predicts the condition of interest.4. The computer implemented method as recited in claim 2 , wherein the objective function includes:a measure of redundancy among the first set of risk factors; anda measure of redundancy between the first set and the second set of risk factors.5. The computer implemented method as recited in claim 2 , wherein the objective function includes a sparsity term to limit the number of selected risk factors from the first set.6. The computer implemented method as recited in claim 2 , wherein combining includes minimizing the objective function using iterative methods.7. The computer implemented method as recited in claim 6 , wherein minimizing includes ...

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Номер записи: 5
04-07-2023 дата публикации

Medical diagnosis system with continuous learning and reasoning

Номер: US0011694800B2
Автор: Maria Eleftherou, Chung-Sheng Li, Shahram Ebadollahi, Francisco Curbera
Принадлежит: International Business Machines Corporation

Performing an operation comprising generating, by a computing system based on data received from a plurality of data sources, a data model describing a patient, wherein the data comprises medical history data of the patient and observation data received by the computing system during observation of at least one medical professional, generating, by the computing system and based on the model applied to the received data, a plurality of candidate diagnoses for the patient, executing, by the computing system, a plurality of simulations of a plurality of candidate treatments generated by the computing system based on the model, and identifying a first candidate treatment of the plurality of candidate treatments that reduces an uncertainty value of the data model below a threshold.

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Номер записи: 6
17-09-2009 дата публикации

Method and Apparatus for Semantic Assisted Rating of Multimedia Content

Номер: US20090234831A1
Автор: Shahram Ebadollahi, Milind Naphade, Apostol Ivanov Natsev, John Richard Smith, Ioana Roxana Stanoi, Jelena Tesic, Lexing Xie
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

The present invention is directed to a method and apparatus for assisting in rating and filtering multimedia content, such as images, videos and sound recordings. One embodiment comprises a computer implemented method for rating the objectionability of specified digital content that comprises one or more discrete content items, wherein the method includes the step of moving the specified content to one or more filtering stages in a succession of filtering stages. After the specified content is moved to a given one of the filtering stages, a rating procedure is carried out to determine whether a rating can be applied to one or more of the content items, and if so, a selected rating is applied to each of the one or more content items. The method further comprises moving content items of the specified content to the next stage in the succession after the given stage, when at least one content item of the specified content remains without rating, after the rating procedure at the given stage ...

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Номер записи: 7
15-01-2015 дата публикации

IDENTIFYING TARGET PATIENTS FOR NEW DRUGS BY MINING REAL-WORLD EVIDENCE

Номер: US20150019232A1
Автор: Shahram Ebadollahi, Jianying Hu, Jimeng Sun, Fei Wang, Ping Zhang, EBADOLLAHI SHAHRAM, HU JIANYING, SUN JIMENG, WANG FEI, ZHANG PING
Принадлежит:

Systems and methods for patient identification include identifying a set of mature drugs similar to a target drug using a processor based on a drug similarity measure. A plurality of outcome models are constructed for each mature drug in the set based on real-world evidence, the plurality of outcome models representing a patient response to each mature drug. A patient response to the target drug is predicted based on the outcome models to identify patients for the target drug. 1. A method for patient identification , comprising:identifying a set of mature drugs similar to a target drug using a processor based on a drug similarity measure;constructing a plurality of outcome models for each mature drug in the set based on real-world evidence, the plurality of outcome models representing a patient response to each mature drug; andpredicting a patient response to the target drug based on the outcome models to identify patients for the target drug.2. The method as recited in claim 1 , wherein the drug similarity measure is based on at least one of chemical structure claim 1 , side effects claim 1 , target proteins and annotation hierarchical distance.3. The method as recited in claim 1 , wherein constructing includes identifying patients who take at least one drug from the set of mature drugs.4. The method as recited in claim 3 , wherein constructing includes determining drug outcomes for each of the patients.5. The method as recited in claim 1 , wherein predicting includes generating response scores for each mature drug in the set representing a patient response to the mature drug.6. The method as recited in claim 5 , further comprising combining the response scores to provide a response score for the target drug claim 5 , wherein the response scores are weighted based on the drug similarity measure.7. The method as recited in claim 6 , wherein combining includes combining the response scores for all of the patients.8. The method as recited in claim 6 , wherein ...

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Номер записи: 8
17-01-2002 дата публикации

Method and apparatus for processing echocardiogram video images

Номер: US20020007117A1
Автор: Shahram Ebadollahi, Shih-Fu Chang, Henry Wu
Принадлежит:

Methods and a system are disclosed for processing an echocardiogram video of a patient's heart. The echocardiogram comprises at least a first sequence of consecutive video frames corresponding to a first view of the patient's heart concatenated with a second sequence of consecutive video frames corresponding to a second view of the patient's heart. The end-diastole phase of the patient's heart is monitored in each frame by detecting the electrocardiograph wave, and a key frame is selected upon the occurrence of the R-wave peak in the electrocardiograph wave in each of the first sequence of consecutive video frames and in the second sequence of consecutive video frames. The shape and color content of the echocardiogram image window is monitored in certain video frames, and a transition is detected when there is a change in the first feature between adjacent frames. A summary is generated which comprises by the video frames corresponding to the end-diastole phase.

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Номер записи: 9
04-02-2003 дата публикации

Method and apparatus for processing echocardiogram video images

Номер: US0006514207B2
Автор: Shahram Ebadollahi, Shih-Fu Chang, Henry Wu, EBADOLLAHI SHAHRAM, CHANG SHIH-FU, WU HENRY
Принадлежит: The Trustees of Columbia University in the City of New York, UNIV COLUMBIA, THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK

Methods and a system are disclosed for processing an echocardiogram video of a patient's heart. The echocardiogram comprises at least a first sequence of consecutive video frames corresponding to a first view of the patient's heart concatenated with a second sequence of consecutive video frames corresponding to a second view of the patient's heart. The end-diastole phase of the patient's heart is monitored in each frame by detecting the electrocardiograph wave, and a key frame is selected upon the occurrence of the R-wave peak in the electrocardiograph wave in each of the first sequence of consecutive video frames and in the second sequence of consecutive video frames. The shape and color content of the echocardiogram image window is monitored in certain video frames, and a transition is detected when there is a change in the first feature between adjacent frames. A summary is generated which comprises by the video frames corresponding to the end-diastole phase.

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Номер записи: 10
10-07-2014 дата публикации

ASSESSING PRACTITIONER VALUE IN MULTI-PRACTITIONER SETTINGS

Номер: US20140195260A1
Автор: Jianying Hu, Fei Wang, Robert K. Sorrentino, Shahram Ebadollahi, HU JIANYING, WANG FEI, SORRENTINO ROBERT K, EBADOLLAHI SHAHRAM, SORRENTINO ROBERT K.
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A plurality of actual outcome data points, including actual outcomes for a plurality of episodes of a process, are obtained for the process. A practitioner-independent baseline outcome is also obtained for the process. For each given one of the actual outcome data points, the given one of the actual outcome data points is equated to the practitioner entity-independent baseline outcome multiplied by a plurality of unknown participating practitioner entity outcome indices for each of a plurality of participating practitioner entities. Each of the participating practitioner entity outcome indices is raised to an exponent including a corresponding one of a plurality of unknown participating practitioner entity type indices, to obtain a plurality of equations. The plurality of equations are solved to obtain estimated values of the unknown participating practitioner entity outcome indices and estimated values of the unknown participating practitioner entity type indices.

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Номер записи: 11
25-02-2014 дата публикации

Method and system for outcome based referral using healthcare data of patient and physician populations

Номер: US0008660857B2
Автор: Shahram Ebadollahi, Jianying Hu, Martin S. Kohn, Jonathan D. Laserson, Hani Neuvirth-Telem, Lavi Shpigelman, Robert K. Sorrentino, EBADOLLAHI SHAHRAM, HU JIANYING, KOHN MARTIN S, LASERSON JONATHAN D, NEUVIRTH-TELEM HANI, SHPIGELMAN LAVI, SORRENTINO ROBERT K, KOHN MARTIN S., LASERSON JONATHAN D., SORRENTINO ROBERT K.
Принадлежит: International Business Machines Corporation, EBADOLLAHI SHAHRAM, HU JIANYING, KOHN MARTIN S, LASERSON JONATHAN D, NEUVIRTH-TELEM HANI, SHPIGELMAN LAVI, SORRENTINO ROBERT K, IBM, KOHN MARTIN S., LASERSON JONATHAN D., SORRENTINO ROBERT K., INTERNATIONAL BUSINESS MACHINES CORPORATION

A recommendation system and method includes extracting patient features for a current patient to generate representation of the current patient. The patient features for the current patient are compared to physician features of one or more physicians and patient-to-physician features of a group of patients from medically related records. Outcome measures associated with physicians are compared related to a current query. A future outcome for patient, physician pairs are predicted for the current patient based upon at least one predictive model constructed from the features and outcome measures to output.

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Номер записи: 12
23-01-2014 дата публикации

SYSTEM AND METHOD FOR COMPOSITE DISTANCE METRIC LEVERAGING MULTIPLE EXPERT JUDGMENTS

Номер: US20140025618A1
Автор: Shahram Ebadollahi, Jimeng Sun, Fei Wang, EBADOLLAHI SHAHRAM, SUN JIMENG, WANG FEI
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

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Номер записи: 13
06-02-2018 дата публикации

Healthcare as a service—downloadable enterprise application

Номер: US0009886255B2
Автор: Houtan Aghili, Ock Kee Baek, Francisco P. Curbera, Shahram Ebadollahi, Shubir Kapoor, Shilpa N. Mahatma, Ajay Mohindra, Aleksandra Mojsilovic, Gigi Y. Yuen-Reed, AGHILI HOUTAN, BAEK OCK KEE, CURBERA FRANCISCO P, EBADOLLAHI SHAHRAM, KAPOOR SHUBIR, MAHATMA SHILPA N, MOHINDRA AJAY, MOJSILOVIC ALEKSANDRA, YUEN REED GIGI Y, Aghili Houtan, Baek Ock Kee, Curbera Francisco P., Ebadollahi Shahram, Kapoor Shubir, Mahatma Shilpa N., Mohindra Ajay, Mojsilovic Aleksandra, Yuen-Reed Gigi Y.
Принадлежит: International Business Machines Corporation, IBM

An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

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Номер записи: 14
21-08-2014 дата публикации

DYNAMIC IDENTIFICATION OF THE BIOMARKERS LEVERAGING THE DYNAMICS OF THE BIOMARKER

Номер: US20140236545A1
Автор: Shahram Ebadollahi, Jianying Hu, Jimeng Sun, Fei Wang, Jiayu Zhou, EBADOLLAHI SHAHRAM, HU JIANYING, SUN JIMENG, WANG FEI, ZHOU JIAYU
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for providing a temporally dynamic model parameter include building a model parameter by minimizing a loss function based on patient measurements taken at a plurality of time points. Temporally related values of the model parameter are identified, using a processor, having a same type of patient measurement taken at different time points. At least one value of the model parameter and temporally related values of the at least one value are selected to provide a temporally dynamic model parameter.

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Номер записи: 15
21-08-2014 дата публикации

DYNAMIC IDENTIFICATION OF THE BIOMARKERS LEVERAGING THE DYNAMICS OF THE BIOMARKER

Номер: US20140236544A1
Автор: Shahram Ebadollahi, Jianying Hu, Jimeng Sun, Fei Wang, Jiayu Zhou, EBADOLLAHI SHAHRAM, HU JIANYING, SUN JIMENG, WANG FEI, ZHOU JIAYU
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for providing a temporally dynamic model parameter include building a model parameter by minimizing a loss function based on patient measurements taken at a plurality of time points. Temporally related values of the model parameter are identified, using a processor, having a same type of patient measurement taken at different time points. At least one value of the model parameter and temporally related values of the at least one value are selected to provide a temporally dynamic model parameter.

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Номер записи: 16
28-09-2021 дата публикации

Personalized intervention based on machine learning of behavior change states

Номер: US0011132920B2
Автор: Marie Angelopoulos, Shahram Ebadollahi, Stewart T. Sill, Michal Rosen-Zvi, Ching-Hua Chen, James V. Codella, Si Sun, ANGELOPOULOS MARIE, EBADOLLAHI SHAHRAM, SILL STEWART T, ROSEN-ZVI MICHAL, CHEN CHING-HUA, CODELLA JAMES V, SUN SI, Angelopoulos, Marie, Ebadollahi, Shahram, Sill, Stewart T., Rosen-Zvi, Michal, Chen, Ching-Hua, Codella, James V., Sun, Si
Принадлежит: International Business Machines Corporation, IBM

A system provides an intervention for a user and comprises at least one processor. The system monitors behavior and context of a user to generate a behavior history. One or more models are utilized to determine an intervention for the user to induce a behavior modification, wherein the one or more models map interventions to user context and behavior and utilize the behavior history to determine an effective intervention for the user. The intervention is provided to the user and feedback is received in response to the intervention. The one or more models are updated based on the feedback. Embodiments of the present invention further include a method and computer program product for providing an intervention to a user in substantially the same manner described above.

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Номер записи: 17
10-11-2020 дата публикации

Dynamic identification of the biomarkers leveraging the dynamics of the biomarker

Номер: US0010832821B2
Автор: Shahram Ebadollahi, Jianying Hu, Jimeng Sun, Fei Wang, Jiayu Zhou, EBADOLLAHI SHAHRAM, HU JIANYING, SUN JIMENG, WANG FEI, ZHOU JIAYU, Ebadollahi, Shahram, Hu, Jianying, Sun, Jimeng, Wang, Fei, Zhou, Jiayu
Принадлежит: International Business Machines Corporation, IBM, INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for providing a temporally dynamic model parameter include building a model parameter by minimizing a loss function based on patient measurements taken at a plurality of time points. Temporally related values of the model parameter are identified, using a processor, having a same type of patient measurement taken at different time points. At least one value of the model parameter and temporally related values of the at least one value are selected to provide a temporally dynamic model parameter.

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Номер записи: 18
22-03-2018 дата публикации

Secure Distributed Patient Consent and Information Management

Номер: US20180082024A1
Автор: Francisco P. Curbera, Shahram Ebadollahi, Maria Eleftheriou, Ramesh Gopinath, Krishna C. Ratakonda, Paul C. Tang
Принадлежит:

Mechanisms are provided for executing patient information transactions. The mechanism store, in a ledger storage system, for each patient, a history of patient consents associated with patient transactions in a healthcare network, comprising patient consent data structures associated with the patient information transferred between participants as part of the transaction. The mechanisms store a master patient record index (MPRI) for each of the patients. The MPRI stores record locators identifying locations of portions of patient information for the patient on different computing devices associated with different health providers. The mechanisms execute, by a transaction manager, a transaction to grant access to a portion of a patient's information based on consent information stored in the ledger storage system and record locators in the MPRI. The mechanisms update, by a ledger storage engine of the data processing system, the history of transactions based on the execution of the transaction. 1. A method , in a data processing system , for executing patient information transactions based on a security protected transaction ledger , comprising:storing, by the data processing system, in a ledger storage system, for each patient, a history of patient consents associated with patient transactions in a healthcare network, comprising patient consent data structures associated with the patient information transferred between participants as part of the transaction;storing, by the data processing system, a master patient record index (MPRI) for each of the patients, wherein the MPRI stores record locators identifying locations of portions of patient information for the patient on different computing devices associated with different health providers;executing, by a transaction manager of the data processing system, a transaction to grant access to a portion of a patient's information based on consent information stored in the ledger storage system and record locators in ...

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Номер записи: 19
27-06-2019 дата публикации

PATIENT ASSISTANT FOR CHRONIC DISEASES AND CO-MORBIDITIES

Номер: US20190198174A1
Автор: Soroush Abbaspour, Francisco P. Curbera, Daniel M. Dias, Shahram Ebadollahi, Maria Eleftheriou, ABBASPOUR SOROUSH, CURBERA FRANCISCO P, DIAS DANIEL M, EBADOLLAHI SHAHRAM, ELEFTHERIOU MARIA, Abbaspour, Soroush, Curbera, Francisco P., Dias, Daniel M., Ebadollahi, Shahram, Eleftheriou, Maria
Принадлежит: International Business Machines Corp

Patient assistant systems are provided. In various embodiments, health data of a user is read from one or more data source. A cohort of the user is determined based on a primary diagnosis of the user. The health data of the user includes the primary diagnosis. A co-morbidity of the primary diagnosis within the cohort is determined. One or more predictor of the co-morbidity within the cohort is determined. Assistance information is provided to the user based on the one or more predictor. The assistance information includes the predictor and one or more recommendation to mitigate the co-morbidity.

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Номер записи: 20
24-10-2013 дата публикации

COMBINING KNOWLEDGE AND DATA DRIVEN INSIGHTS FOR IDENTIFYING RISK FACTORS IN HEALTHCARE

Номер: US20130282393A1
Автор: Shahram Ebadollahi, Jianying Hu, Dijun Luo, Marianthi Markatou, Jimeng Sun, Fei Wang
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

Systems and methods for risk factor identification include identifying a first set of risk factors from personal data. A second set of risk factors is identified from at least one of a user input and a knowledge source. The first set is combined with the second set, using a processor, by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest. 1. A system for risk factor identification , comprising:a data processing module configured to identify a first set of risk factors from personal data;a knowledge based processing module configured to identify a second set of risk factors from at least one of a user input and a knowledge source; anda processor configured to implement an augmentation module, the augmentation module configured to combine the first set with the second set by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest.2. The system as recited in claim 1 , wherein the augmentation module is further configured to model the first set and the second set as an objective function.3. The system as recited in claim 2 , wherein the objective function includes a regression model as a reconstruction error representing how accurate the combined list of risk factors predicts the condition of interest.4. The system as recited in claim 2 , wherein the objective function includes:a measure of redundancy among the first set of risk factors; anda measure of redundancy between the first set and the second set of risk factors.5. The system as recited in claim 2 , wherein the objective function includes a sparsity term to limit the number of selected risk factors from the first set.6. The system as recited in claim 2 , wherein the augmentation module is further configured to minimize the objective function using iterative ...

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Номер записи: 21
06-06-2013 дата публикации

ASSESSING PRACTITIONER VALUE IN MULTI-PRACTITIONER SETTINGS

Номер: US20130144639A1
Автор: Jianying Hu, Fei Wang, Robert K. Sorrentino, Shahram Ebadollahi
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A plurality of actual outcome data points, including actual outcomes for a plurality of episodes of a process, are obtained for the process. A practitioner-independent baseline outcome is also obtained for the process. For each given one of the actual outcome data points, the given one of the actual outcome data points is equated to the practitioner entity-independent baseline outcome multiplied by a plurality of unknown participating practitioner entity outcome indices for each of a plurality of participating practitioner entities. Each of the participating practitioner entity outcome indices is raised to an exponent including a corresponding one of a plurality of unknown participating practitioner entity type indices, to obtain a plurality of equations. The plurality of equations arc solved to obtain estimated values of the unknown participating practitioner entity outcome indices and estimated values of the unknown participating practitioner entity type indices.

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Номер записи: 22
22-03-2018 дата публикации

Secure Distributed Patient Consent and Information Management

Номер: US20180082023A1
Автор: Francisco P. Curbera, Shahram Ebadollahi, Maria Eleftheriou, Ramesh Gopinath, Krishna C. Ratakonda, Paul C. Tang
Принадлежит:

Mechanisms are provided to implement secure distributed patient consent and patient information management that addresses the competing needs for efficient access to electronic medical records by authorized parties while maintaining protection of privacy of patient health related information and complying with governing regulations. The mechanisms of the illustrative embodiments implement a tamper-proof and immutable ledger storage system to manage patient consent information and distribution of patient information based on the patient consent information. The ledger storage system operates in conjunction with a master patient record index (MPRI) component to enable the exchange of patient information among health providers once consent has been granted by the patient. Once provided with a record locator from the MPRI, a health provider can directly request patient information from another health provider, where the patient information resides as indicated by the record locator, or an intermediary data hub implementation may be utilized. 1. A method , in a data processing system comprising at least one processor and at least one memory , the memory comprising instructions which are executed by the at least one processor to specifically configure the at least one processor to implement a distributed patient consent and information management system (CIMS) , the method comprising:receiving, by the CIMS of the data processing system, a request to perform a transaction of patient information for a patient to provide the patient information to a first participant device;distributing, by the CIMS, the request to a plurality of node devices of a validation network for validation of the transaction, wherein the validation is based on correlating a patient consent data structure with the patient information and the first participant device;receiving, by the CIMS, a response from the plurality of node devices indicating whether or not the transaction is validated;in response ...

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Номер записи: 23
04-10-2011 дата публикации

Method and apparatus for semantic assisted rating of multimedia content

Номер: US0008032539B2
Автор: Shahram Ebadollahi, Milind Naphade, Apostol Ivanov Natsev, John Richard Smith, Ioana Roxana Stanoi, Jelena Tesic, Lexing Xie, EBADOLLAHI SHAHRAM, NAPHADE MILIND, NATSEV APOSTOL IVANOV, SMITH JOHN RICHARD, STANOI IOANA ROXANA, TESIC JELENA, XIE LEXING
Принадлежит: International Business Machines Corporation, IBM, INTERNATIONAL BUSINESS MACHINES CORPORATION

The present invention is directed to a method and apparatus for assisting in rating and filtering multimedia content, such as images, videos and sound recordings. One embodiment comprises a computer implemented method for rating the objectionability of specified digital content that comprises one or more discrete content items, wherein the method includes the step of moving the specified content to one or more filtering stages in a succession of filtering stages. After the specified content is moved to a given one of the filtering stages, a rating procedure is carried out to determine whether a rating can be applied to one or more of the content items, and if so, a selected rating is applied to each of the one or more content items. The method further comprises moving content items of the specified content to the next stage in the succession after the given stage, when at least one content item of the specified content remains without rating, after the rating procedure at the given stage ...

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Номер записи: 24
19-05-2016 дата публикации

HEALTHCARE AS A SERVICE - DOWNLOADABLE ENTERPRISE APPLICATION

Номер: US20160140362A1
Автор: Houtan Aghili, Ock Kee Baek, Francisco P. Curbera, Shahram Ebadollahi, Shubir Kapoor, Shilpa N. Mahatma, Ajay Mohindra, Aleksandra Mojsilovic, Gigi Y. Yuen-Reed, AGHILI HOUTAN, BAEK OCK KEE, CURBERA FRANCISCO P, EBADOLLAHI SHAHRAM, KAPOOR SHUBIR, MAHATMA SHILPA N, MOHINDRA AJAY, MOJSILOVIC ALEKSANDRA, YUEN-REED GIGI Y, CURBERA FRANCISCO P., MAHATMA SHILPA N., YUEN-REED GIGI Y.
Принадлежит:

An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment. 1. A method of providing an application as a service in a secure environment , comprising:creating a sandbox in a user's computing environment;downloading an application to the user's computing environment to run within the sandbox;searching data sources associated with the user's computing environment and establishing connectivity with data registry of the data sources based on data description received with the application;installing the application to run within the sandbox using the established connectivity.2. The method of claim 1 , further comprising:metering usage of the application at the user's computing environment.3. The method of claim 1 , wherein the application comprises database claim 1 , visualization and analytics components.4. The method of claim 1 , wherein the sandbox allows access to data local to the user's computing environment and prevents the data from leaving the user's computing environment.5. The method of claim 1 , further comprising automatically validating an installation of the application by discovering data specified in the data description in the data sources and determining whether the data specified in the data description exist in the data sources.6. The method of claim 1 , wherein the application is downloaded from a computing environment that provides the application as SaaS.7. The method of claim 1 , wherein a user interface is ...

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Номер записи: 25
12-09-2017 дата публикации

Healthcare as a service—downloadable enterprise application

Номер: US0009760359B2
Автор: Houtan Aghili, Ock Kee Baek, Francisco P. Curbera, Shahram Ebadollahi, Shubir Kapoor, Shilpa N. Mahatma, Ajay Mohindra, Aleksandra Mojsilovic, Gigi Y. Yuen-Reed, AGHILI HOUTAN, BAEK OCK KEE, CURBERA FRANCISCO P, EBADOLLAHI SHAHRAM, KAPOOR SHUBIR, MAHATMA SHILPA N, MOHINDRA AJAY, MOJSILOVIC ALEKSANDRA, YUEN-REED GIGI Y, Aghili Houtan, Baek Ock Kee, Curbera Francisco P., Ebadollahi Shahram, Kapoor Shubir, Mahatma Shilpa N., Mohindra Ajay, Mojsilovic Aleksandra, Yuen-Reed Gigi Y.
Принадлежит: International Business Machines Corporation, IBM

An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

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Номер записи: 26
19-05-2016 дата публикации

HEALTHCARE AS A SERVICE - DOWNLOADABLE ENTERPRISE APPLICATION

Номер: US20160139903A1
Автор: Houtan Aghili, Ock Kee Baek, Francisco P. Curbera, Shahram Ebadollahi, Shubir Kapoor, Shilpa N. Mahatma, Ajay Mohindra, Aleksandra Mojsilovic, Gigi Y. Yuen-Reed, AGHILI HOUTAN, BAEK OCK KEE, CURBERA FRANCISCO P, EBADOLLAHI SHAHRAM, KAPOOR SHUBIR, MAHATMA SHILPA N, MOHINDRA AJAY, MOJSILOVIC ALEKSANDRA, YUEN-REED GIGI Y, CURBERA FRANCISCO P., MAHATMA SHILPA N., YUEN-REED GIGI Y.
Принадлежит:

An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment. 17.-. (canceled)8. A computer readable storage medium storing a program of instructions executable by a machine to perform a method of providing an application as a service in a secure environment , comprising:creating a sandbox in a user's computing environment;downloading an application to the user's computing environment to run within the sandbox;searching data sources associated with the user's computing environment and establishing connectivity with data registry of the data sources based on data description received with the application;installing the application to run within the sandbox using the established connectivity.9. The computer readable storage medium of claim 8 , further comprising:metering usage of the application at the user's computing environment.10. The computer readable storage medium of claim 8 , wherein the application comprises database claim 8 , visualization and analytics components.11. The computer readable storage medium of claim 8 , wherein the sandbox allows access to data local to the user's computing environment and prevents the data from leaving the user's computing environment.12. The computer readable storage medium of claim 8 , further comprising automatically validating an installation of the application by discovering data specified in the data description in the data sources and determining whether the data specified in the data ...

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Номер записи: 27
15-01-2015 дата публикации

IDENTIFYING TARGET PATIENTS FOR NEW DRUGS BY MINING REAL-WORLD EVIDENCE

Номер: US20150019239A1
Автор: Shahram Ebadollahi, Jianying Hu, Jimeng Sun, Fei Wang, Ping Zhang, EBADOLLAHI SHAHRAM, HU JIANYING, SUN JIMENG, WANG FEI, ZHANG PING
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

Systems and methods for patient identification include identifying a set of mature drugs similar to a target drug using a processor based on a drug similarity measure. A plurality of outcome models are constructed for each mature drug in the set based on real-world evidence, the plurality of outcome models representing a patient response to each mature drug. A patient response to the target drug is predicted based on the outcome models to identify patients for the target drug. 1. A computer readable storage medium comprising a computer readable program for patient identification , wherein the computer readable program when executed on a computer causes the computer to perform the steps of:identifying a set of mature drugs similar to a target drug based on a drug similarity measure;constructing a plurality of outcome models for each mature drug in the set based on real-world evidence, the plurality of outcome models representing a patient response to each mature drug; andpredicting a patient response to the target drug based on the outcome models to identify patients for the target drug.2. A system for patient identification , comprising:a similarity module configured to identify a set of mature drugs similar to a target drug using a processor based on a drug similarity measure;a modeling module configured to construct a plurality of outcome models for each mature drug in the set based on real-world evidence, the plurality of outcome models representing a patient response to each mature drug; anda prediction module configured to predict a patient response to the target drug based on the outcome models to identify patients for the target drug.3. The system as recited in claim 2 , wherein the drug similarity measure is based on at least one of chemical structure claim 2 , side effects claim 2 , target proteins and annotation hierarchical distance.4. The system as recited in claim 2 , wherein the modeling module is further configured to identify patients who take at ...

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Номер записи: 28
12-11-2013 дата публикации

Mining temporal patterns in longitudinal event data using discrete event matrices and sparse coding

Номер: US0008583586B2
Автор: Shahram Ebadollahi, Jianying Hu, Martin S. Kohn, Noah Lee, Robert K. Sorrentino, Jimeng Sun, Fei Wang, EBADOLLAHI SHAHRAM, HU JIANYING, KOHN MARTIN S, LEE NOAH, SORRENTINO ROBERT K, SUN JIMENG, WANG FEI, KOHN MARTIN S., SORRENTINO ROBERT K.
Принадлежит: International Business Machines Corporation, EBADOLLAHI SHAHRAM, HU JIANYING, KOHN MARTIN S, LEE NOAH, SORRENTINO ROBERT K, SUN JIMENG, WANG FEI, IBM, KOHN MARTIN S., SORRENTINO ROBERT K., INTERNATIONAL BUSINESS MACHINES CORPORATION

Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.

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Номер записи: 29
14-11-2019 дата публикации

MEDICAL DIAGNOSIS SYSTEM WITH CONTINUOUS LEARNING AND REASONING

Номер: US20190348178A1
Автор: Maria Eleftherou, Chung-Sheng Li, Shahram Ebadollahi, Francisco Curbera
Принадлежит: International Business Machines Corp

Performing an operation comprising generating, by a computing system based on data received from a plurality of data sources, a data model describing a patient, wherein the data comprises medical history data of the patient and observation data received by the computing system during observation of at least one medical professional, generating, by the computing system and based on the model applied to the received data, a plurality of candidate diagnoses for the patient, executing, by the computing system, a plurality of simulations of a plurality of candidate treatments generated by the computing system based on the model, and identifying a first candidate treatment of the plurality of candidate treatments that reduces an uncertainty value of the data model below a threshold.

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Номер записи: 30
19-07-2016 дата публикации

System and method for composite distance metric leveraging multiple expert judgments

Номер: US0009396439B2
Автор: Shahram Ebadollahi, Jimeng Sun, Fei Wang, EBADOLLAHI SHAHRAM, SUN JIMENG, WANG FEI
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION, IBM

A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert and each neighborhood represents an individual similarity measure of the expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

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Номер записи: 31
11-12-2008 дата публикации

METHOD AND APPARATUS FOR AUTOMATIC MULTIMEDIA NARRATIVE ENRICHMENT

Номер: US20080306925A1
Автор: Murray S. Campbell, Shahram Ebadollahi, Matthew L. Hill, Brian Michael Landry, Chung-Sheng Li, Apostol Ivanov Natsev, Milind R. Naphade, John R. Smith, Jelena Tesic, Lexing Xie
Принадлежит:

A method and apparatus is disclosed that receives an input narrative in a particular media format, and produces therefrom a multimedia enriched version of the input narrative. In one embodiment, a method is provided for enriching an input narrative with multimedia content, wherein the method includes the step of selectively segmenting the input narrative to form queries pertaining to different portions or elements of the input narrative. The method further comprises retrieving multimedia artifacts from one or more multimedia repositories, wherein each retrieved multimedia artifact is associated with one of the queries, and selecting a subset of the retrieved multimedia artifacts, wherein the subset includes artifacts comprising different types of multimedia content. The input narrative is then combined with respective multimedia artifacts of the subset, in order to provide an enriched and enhanced narrative.

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Номер записи: 32
22-10-2013 дата публикации

System and method for composite distance metric leveraging multiple expert judgments

Номер: US0008566268B2
Автор: Shahram Ebadollahi, Jimeng Sun, Fei Wang, EBADOLLAHI SHAHRAM, SUN JIMENG, WANG FEI
Принадлежит: International Business Machines Corporation, EBADOLLAHI SHAHRAM, SUN JIMENG, WANG FEI, IBM, INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

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Номер записи: 33
29-04-2010 дата публикации

SYSTEM AND METHOD FOR ORGANIZING AND DISPLAYING OF LONGITUDINAL MULTIMODAL MEDICAL RECORDS

Номер: US20100106522A1
Автор: James W. Cooper, Youssef Drissi, Shahram Ebadollahi, Anthony Tom Levas, COOPER JAMES W, DRISSI YOUSSEF, EBADOLLAHI SHAHRAM, LEVAS ANTHONY TOM, COOPER JAMES W.
Принадлежит:

A system and method for processing data includes organizing medical information in a concept frame data structure, which is adapted to include medical measurements and related metadata. The medical information is analyzed to extract further information using information extractors and to store extracted medical information in the concept frame data structure. References are stored to appropriate visualization methods along with an associated concept in the concept frame data structure.

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Номер записи: 34
05-08-2014 дата публикации

System and method for organizing and displaying of longitudinal multimodal medical records

Номер: US0008799286B2
Автор: James W. Cooper, Youssef Drissi, Shahram Ebadollahi, Anthony Tom Levas
Принадлежит: International Business Machines Corporation

A system and method for processing data includes organizing medical information in a concept frame data structure, which is adapted to include medical measurements and related metadata. The medical information is analyzed to extract further information using information extractors and to store extracted medical information in the concept frame data structure. References are stored to appropriate visualization methods along with an associated concept in the concept frame data structure.

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Номер записи: 35
05-09-2013 дата публикации

METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR AGGREGATING POPULATION DATA

Номер: US20130231953A1
Автор: Shahram Ebadollahi, Jianying HU, Jimeng Sun, Robert K. Sorrentino
Принадлежит:

A system, method and program product for matching members of a population, e.g., patients, based on member similarities. Patients are mapped to a bipartite graph with patient nodes connected by weighted edges to clustered factor nodes, are clustered categorically. As a new patient query is received, a similarity measure for each other patient is generated for each cluster by comparing cluster edges. The cluster similarity measures are aggregated for each patient to provide a global closeness measure to every other patient. Based on the global closeness measure, a list of the closest patients is displayed and measurement feedback may be provided. 1. A system for ordering members of a population , said system comprising:a similarity measurement module listing members of a population responsive to comparison of member features;a similarity match module selectively presenting a number of members as the closest matches to one member; anda feedback module receiving feedback about the presented closest matches.2. A system as in claim 1 , wherein said similarity measurement module graphically maps the relationship between each member and each feature claim 1 , and said similarity measurement module weights the mapped relationship.3. A system as in claim 2 , wherein said plurality of features are clustered and said similarity measurement module determines for each other member a similarity measure for each cluster for said one member.4. A system as in claim 3 , wherein said similarity measurement module determines a global similarity measure between said one member and said each other member claim 3 , said global similarity measure being the aggregation of cluster similarity measures for claim 3 , and indicating the closeness to claim 3 , said each other member claim 3 , said similarity measurement module selectively storing a list of matches and corresponding global similarity measures.5. A system as in claim 4 , wherein said similarity list of matches includes a second ...

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Номер записи: 36
26-07-2012 дата публикации

MINING TEMPORAL PATTERNS IN LONGITUDINAL EVENT DATA USING DISCRETE EVENT MATRICES AND SPARSE CODING

Номер: US20120191640A1
Автор: Shahram Ebadollahi, Jiaying Hu, Martin S. Kohn, Noah Lee, Robert K. Sorrentino, Jimeng Sun, Fei Wang, EBADOLLAHI SHAHRAM, HU JIAYING, KOHN MARTIN S, LEE NOAH, SORRENTINO ROBERT K, SUN JIMENG, WANG FEI, KOHN MARTIN S., SORRENTINO ROBERT K.
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework. 1. A method for event pattern mining comprising:representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type; andperforming temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.2. The method of claim 1 , wherein said representing further comprises mapping event information from a probabilistic event space to said measurable geometric space.3. The method of claim 1 , wherein said performing temporal event pattern mining further comprises online non-negative matrix factorization.4. The method of claim 1 , further comprising refining event patters using user feedback.5. The method of claim 1 , wherein performing temporal event pattern mining further comprises extracting individual latent temporal patterns in the form of feature images and activation codes from data for an entity.6. The method of claim 1 , wherein sparsity is enforced in the geometric representation using one or more regularizers.7. The method of claim 1 , wherein the sparse TEMR is constrained to prevent trivial solutions.8. The method of claim 1 , wherein performing temporal event pattern mining further comprises clustering multiple entities into pattern groups using exploratory analytic learning.9. The method of claim 1 , wherein performing temporal event ...

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Номер записи: 37
16-02-2012 дата публикации

SYSTEM AND METHOD FOR PREDICTING NEAR-TERM PATIENT TRAJECTORIES

Номер: US20120041277A1
Автор: Ebadollahi Shahram, HU Jianying, Sorrentino Robert K., Sow Daby M., Sun Jimeng
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for predicting near term measurements of a patient includes a stream processor configured to summarize raw measurements from patients into signatures and construct optimal prediction models based on previously obtained signatures. A similar patient tracker is configured to monitor similar patient information for a query patient. The similar patient information is determined based on a similarity between the query patient and signatures of other patients. A model analyzer is configured to employ retrofitted optimal prediction models from similar patients to predict near term measurements of the query patient. 1. A system to predict near term measurements of a patient , comprising:a stream processor configured to summarize raw measurements from patients into signatures and construct optimal prediction models using previously obtained signatures;a similar patient tracker configured to monitor similar patient information relative to a query patient, the similar patient information being determined based on a similarity between the query patient and the signatures of other patients; anda model analyzer configured to employ retrofitted optimal prediction models from similar patients to predict near term measurements of the query patient.2. The system as recited in claim 1 , wherein the stream processor summarizes raw measurements in real-time or near real-time.3. The system as recited in claim 1 , wherein the signatures include frequency domain coefficients which represent time windows of a time series of measurements representing health status for a given patient.4. The system as recited in claim 3 , wherein the time series of measurements includes one or more of heart rate claim 3 , blood pressure claim 3 , blood oxygen claim 3 , electrocardiogram information and temperature.5. The system as recited in claim 1 , wherein the similar patient tracker updates which optimal prediction models that are employed to predict near term measurements of the query ...

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Номер записи: 38
03-05-2012 дата публикации

METHOD AND SYSTEM FOR OUTCOME BASED REFERRAL USING HEALTHCARE DATA OF PATIENT AND PHYSICIAN POPULATIONS

Номер: US20120109683A1
Автор: Ebadollahi Shahram, HU Jianying, Kohn Martin S., Laserson Jonathan D., Neuvirth-Telem Hani, Shpigelman Lavi, Sorrentino Robert K.
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A recommendation system and method includes extracting patient features for a current patient to generate representation of the current patient. The patient features for the current patient are compared to physician features of one or more physicians and patient-to-physician features of a group of patients from medically related records. Outcome measures associated with physicians are compared related to a current query. A future outcome for patient, physician pairs are predicted for the current patient based upon at least one predictive model constructed from the features and outcome measures to output. 1. A recommendation method , comprising:extracting patient features for a current patient to generate representation of the current patient;comparing the patient features for the current patient to physician features of one or more physicians and patient-to-physician features of a group of patients from medically related records;comparing outcome measures associated with physicians related to a current query; andpredicting a future outcome for patient, physician pairs for the current patient based upon at least one predictive model constructed from the features and outcome measures to output.2. The method as recited in claim 1 , wherein extracting patient features includes extracting patient features of a current patient from a patient profile including biographical patient data.3. The method as recited in claim 1 , wherein extracting patient features includes selecting relevant features.4. The method as recited in claim 1 , further comprising extracting physician features from physician profiles including medical practice information and patient treatment information.5. The method as recited in claim 1 , further comprising extracting patient-to-physician features including outcomes of similar patients treated by the one or more physicians.6. The method as recited in claim 1 , wherein comparing outcome measures includes collecting statistics from medical literature ...

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Номер записи: 39
16-08-2012 дата публикации

DETECTING UNEXPECTED HEALTHCARE UTILIZATION BY CONSTRUCTING CLINICAL MODELS OF DOMINANT UTILIZATION GROUPS

Номер: US20120209620A1
Автор: Ebadollahi Shahram, HU Jianying, Sorrentino Robert K., WANG FEI
Принадлежит: INTERNATIONAL BUSINESS MACHINES CORPORATION

A system and method for identifying unexpected utilization profiles at a patient level includes determining one or more clusters that have a profile based on patient profiles and building a representative model for each cluster including demographic and clinical information. Using the model, demographic and clinical characteristics are determined which form expected utilization cluster. An expected utilization cluster for each patient, which is derived from the demographic features and the clinical characteristics, is compared against an actual utilization profile for that patient to determine whether the actual utilization profile is unexpected. 1. A method for identifying unexpected utilization profiles at a patient level , comprising:determining one or more clusters that have a profile based on patient profiles;building a representative model for each cluster including demographic and clinical information;using the model to determine what demographic and clinical characteristics determine an expected utilization cluster; andcomparing an expected utilization cluster for each patient derived from the demographic features and the clinical characteristics against an actual utilization profile for that patient to determine whether the actual utilization profile is unexpected.2. The method as recited in claim 1 , wherein determining one or more clusters includes clustering a patient population by employing a classification and regression tree (CART) method.3. The method as recited in claim 2 , wherein clustering includes employing a modified Hierarchical Agglomerative Clustering (HAC) method.4. The method as recited in claim 2 , wherein clustering includes determining a super-patient having characteristics of all patients in a cluster.5. The method as recited in claim 1 , further comprising addressing cluster imbalances by employing threshold criterion and a modified Hierarchical Agglomerative Clustering (HAC) method.6. The method as recited in claim 1 , wherein ...

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Номер записи: 40
02-07-2015 дата публикации

System and method for composite distance metric leveraging multiple expert judgments

Номер: US20150186788A1
Автор: Fei Wang, Jimeng Sun, Shahram Ebadollahi
Принадлежит: International Business Machines Corp

A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert and each neighborhood represents an individual similarity measure of the expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

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Номер записи: 41
08-01-2004 дата публикации

Method and apparatus for processing echocardiogram video images

Номер: WO2001078492A3
Автор: Henry D Wu, Shahram Ebadollahi, Shih-Fu Chang
Принадлежит: Univ Columbia

Methods and a system are disclosed for processing an echocardiogram video of a patient's heart. The echocardiogram comprises at least a first sequence of consecutive video frames corresponding to a first view of the patient's heart concatenated with a second sequence of consecutive video frames corresponding to a second view of the patient's heart. The end-diastole phase of the patient's heart is monitored in each frame by detecting the electrocardiograph wave, and a key frame is selected upon the occurence of the R-wave peak in the electrocardiograph wave in each of the first sequence of consecutive video frames and in the second sequence of consecutive video frames. The shape and color content of the echocardiogram image window is monitored in certain video frames, and a transition is detected when there is a change in the first feature between adjacent frames. A summary is generated which comprises by the video frames corresponding to the end-diastole phase.

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Номер записи: 42
12-04-2012 дата публикации

System and method for composite distance metric leveraging multiple expert judgments

Номер: US20120089551A1
Автор: Fei Wang, Jimeng Sun, Shahram Ebadollahi
Принадлежит: International Business Machines Corp

A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

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Номер записи: 43