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

Clinical Information and Decision Making (1915) Machine Learning (2076) Artificial Intelligence (2129) Decision Support for Health Professionals (1539) Electronic Health Records (1319)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24996, first published .
Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study

Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study

Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study

Authors of this article:

Haichen Lv1 Author Orcid Image ;   Xiaolei Yang1 Author Orcid Image ;   Bingyi Wang2 Author Orcid Image ;   Shaobo Wang3, 4 Author Orcid Image ;   Xiaoyan Du2 Author Orcid Image ;   Qian Tan5 Author Orcid Image ;   Zhujing Hao1 Author Orcid Image ;   Ying Liu1 Author Orcid Image ;   Jun Yan4 Author Orcid Image ;   Yunlong Xia1 Author Orcid Image
Article Authors Cited by (24) Tweetations (2) Metrics

Journals

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  10. Wang S, Du X, Liu G, Xing H, Jiao Z, Yan J, Liu Y, Lv H, Xia Y. An Interpretable Data-Driven Medical Knowledge Discovery Pipeline Based on Artificial Intelligence. IEEE Journal of Biomedical and Health Informatics 2023;27(10):5099 View
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  15. Hu Y, Ma F, Hu M, Shi B, Pan D, Ren J. Development and validation of a machine learning model to predict the risk of readmission within one year in HFpEF patients. International Journal of Medical Informatics 2025;194:105703 View
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  17. Yan L, Zhang J, Chen L, Zhu Z, Sheng X, Zheng G, Yuan J. Predictive Value of Machine Learning for the Risk of In‐Hospital Death in Patients With Heart Failure: A Systematic Review and Meta‐Analysis. Clinical Cardiology 2025;48(1) View
  18. Hajishah H, Kazemi D, Safaee E, Amini M, Peisepar M, Tanhapour M, Tavasol A. Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis. BMC Cardiovascular Disorders 2025;25(1) View
  19. Wang C, Song D, Dong J, Zhao Y, Liu Y, Gao J, Cui Z, Li C. Dynamic Prediction of Cardiovascular Death among Old People with Mildly Reduced Kidney Function Using Deep Learning Models Based on a Prospective Cohort Study. Gerontology 2025;71(6):474 View
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  21. Alnomasy N, Pangket P, Mostoles R, Alrashedi H, Pasay-an E, Cho H, Alsayed S, Gonzales A, Alharbi A, Alatawi N, Torres S, Abudawood K, Alamoudi F. Predictive Performance of Machine Learning Models for Heart Failure Readmission: A Systematic Review. Biomedicines 2025;13(9):2111 View
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Conference Proceedings

  1. S M, Murthy M, Kodipalli A. 2024 First International Conference for Women in Computing (InCoWoCo). Enhancing Hospital Mortality Prediction for Heart Failure Patients through Hyperparameter Optimization and Interpretability Analysis with LIME and SHAP View