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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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| Udgivet i: | ESC Heart Fail |
|---|---|
| Main Authors: | , , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
John Wiley and Sons Inc.
2019
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| Fag: | |
| Online adgang: | 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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