Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality

AIMS: This study aimed to review the performance of machine learning (ML) methods compared with conventional statistical models (CSMs) for predicting readmission and mortality in patients with heart failure (HF) and to present an approach to formally evaluate the quality of studies using ML algorith...

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Bibliografiske detaljer
Udgivet i:ESC Heart Fail
Main Authors: Shin, Sheojung, Austin, Peter C., Ross, Heather J., Abdel‐Qadir, Husam, Freitas, Cassandra, Tomlinson, George, Chicco, Davide, Mahendiran, Meera, Lawler, Patrick R., Billia, Filio, Gramolini, Anthony, Epelman, Slava, Wang, Bo, Lee, Douglas S.
Format: Artigo
Sprog:Inglês
Udgivet: John Wiley and Sons Inc. 2020
Fag:
Original Research Articles
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7835549/
https://ncbi.nlm.nih.gov/pubmed/33205591
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/ehf2.13073
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