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

Decision Support for Health Professionals (1462) Clinical Information and Decision Making (1804) Machine Learning (1958) Cardiac Disease Management (143) Heart Failure Self-Management (173) New Methods (1097) Cardiac Risk and Cardiac Risk Calculators (91) Computer-Aided Diagnosis (219)

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
Article Authors Cited by (2) Tweetations Metrics

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