Invention Application
- Patent Title: AUTOMATED DETECTION AND MANAGEMENT OF VAVLULAR HEART DISEASE USING MACHINE LEARNING
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Application No.: US18313931Application Date: 2023-05-08
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Publication No.: US20240379239A1Publication Date: 2024-11-14
- Inventor: Eigil Samset , Xiang Li , Quanzheng Li , Michael H. Picard , Hui Ren , Carola Alejandra Maraboto Gonzalez , Jerome Charton , Abhijit Patil , Mark James Perkins
- Applicant: GE Precision Healthcare LLC , Partners HealthCare System, Inc. , The General Hospital Corporation , The Brigham and Women’s Hospital, Inc.
- Applicant Address: US WI Wauwatosa; US MA Boston; US MA Boston; US MA Boston
- Assignee: GE Precision Healthcare LLC,Partners HealthCare System, Inc.,The General Hospital Corporation,The Brigham and Women’s Hospital, Inc.
- Current Assignee: GE Precision Healthcare LLC,Partners HealthCare System, Inc.,The General Hospital Corporation,The Brigham and Women’s Hospital, Inc.
- Current Assignee Address: US WI Wauwatosa; US MA Boston; US MA Boston; US MA Boston
- Main IPC: G16H50/30
- IPC: G16H50/30 ; G16H10/60 ; G16H50/70

Abstract:
Techniques are described for computer-implemented techniques for managing various aspects of the cardiac care pathway using machine learning. According to an embodiment, a method can include training an outcomes forecasting model to predict patient outcomes resulting from undergoing a cardiac valve procedure using multi-modal training data for a plurality of different patients, wherein the training comprising separately training different machine learning sub-models of the forecasting model to predict preliminary patient outcome data and mapping the preliminary patient outcome data to the patient outcomes, resulting in a trained version of the outcome forecasting model. The method further includes applying the trained version of the outcomes forecasting model to new multi-modal data for a new patient to predict the patient outcomes for the new patient resulting from undergoing the cardiac value procedure.
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