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Machine learning‐based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics

AIMS: Machine learning (ML) is widely believed to be able to learn complex hidden interactions from the data and has the potential in predicting events such as heart failure (HF) readmission and death. Recent studies have revealed conflicting results likely due to failure to take into account the cl...

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Shranjeno v:
Bibliografske podrobnosti
izdano v:ESC Heart Fail
Main Authors: Awan, Saqib Ejaz, Bennamoun, Mohammed, Sohel, Ferdous, Sanfilippo, Frank Mario, Dwivedi, Girish
Format: Artigo
Jezik:Inglês
Izdano: John Wiley and Sons Inc. 2019
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC6437443/
https://ncbi.nlm.nih.gov/pubmed/30810291
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/ehf2.12419
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