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| Predicting Hospital Readmission in Heart Failure Patients in Iran: A Comparison of Various Machine Learning Methods |
| Roya Najafi-Vosough, Javad Faradmal, Seyed Kianoosh Hosseini, Abbas Moghimbeigi, Hossein Mahjub |
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Healthc Inform Res. 2021;27(4):307-314. Published online October 31, 2021 DOI: https://doi.org/10.4258/hir.2021.27.4.307 |
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Predicting Hospital Readmission in Heart Failure Patients in Iran: A Comparison of Various Machine Learning Methods Healthcare Informatics Research. 2021;27(4):307-314  Predicting 90-day readmission for patients with heart failure: a machine learning approach using XGBoost . 2022; Invasive, Non‐Invasive, Machine Learning, and Artificial Intelligence Based Methods for Prediction of Heart Failure Predicting Heart Failure. 2022;1-22 Applications of Machine Learning for Predicting Heart Failure Predicting Heart Failure. 2022;171-188 Frontmatter Predicting Heart Failure. 2022; Index Predicting Heart Failure. 2022;321-325 Machine learning and statistical methods for predicting mortality in heart failure Heart Failure Reviews. 2020;26(3):545-552 Predicting all-cause 90-day hospital readmission for dental patients using machine learning methods BDJ Open. 2021;7(1): Predicting Hospital Readmission of Diabetic Patients Using Machine Learning Frontiers in Health Informatics. 2021;10(1):74 Risk Stratification for Hospital Readmission of Heart Failure Patients Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. 2016; |
