This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1222) Clinical Information and Decision Making (1454) Machine Learning (1521) Cardiac Disease Management (103) Heart Failure Self-Management (158) New Methods (970) Cardiac Risk and Cardiac Risk Calculators (50) Computer-Aided Diagnosis (140)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58812, first published .
Enhancing Clinical Decision Making by Predicting Readmission Risk in Patients With Heart Failure Using Machine Learning: Predictive Model Development Study

Enhancing Clinical Decision Making by Predicting Readmission Risk in Patients With Heart Failure Using Machine Learning: Predictive Model Development Study

Enhancing Clinical Decision Making by Predicting Readmission Risk in Patients With Heart Failure Using Machine Learning: Predictive Model Development Study

Authors of this article:

Xiangkui Jiang1 Author Orcid Image ;   Bingquan Wang1 Author Orcid Image
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