Machine Learning Model for Readmission Prediction of Patients With Heart Failure Based on Electronic Health Records: Protocol for a Quasi-Experimental Study for Impact Assessment

Machine Learning Model for Readmission Prediction of Patients With Heart Failure Based on Electronic Health Records: Protocol for a Quasi-Experimental Study for Impact Assessment

BackgroundCare for patients with heart failure (HF) causes a substantial load on health care systems where a prominent challenge is the elevated rate of readmissions within 30 days following initial discharge. Clinical professionals face high levels of uncertainty and subject...

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Bibliographic Details
Main Authors: Monika Nair, Lina E Lundgren, Amira Soliman, Petra Dryselius, Ebba Fogelberg, Marcus Petersson, Omar Hamed, Miltiadis Triantafyllou, Jens Nygren
Format: Article
Language:English
Published: JMIR Publications 2024-03-01
Series:JMIR Research Protocols
Online Access:https://www.researchprotocols.org/2024/1/e52744

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https://www.researchprotocols.org/2024/1/e52744

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