Enhancing heatstroke prediction accuracy with interpretable machine learning: a multi-center data-driven approach
Background Heatstroke poses a significant threat to public health, frequently culminating in fatal outcomes. This study aimed to develop and validate an interpretable machine learning (ML) model to forecast heatstroke using clinical and laboratory data. Methods Data were collated from 24 hospitals s...
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| Hlavní autoři: | , , , , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
PeerJ Inc.
2025-11-01
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| Edice: | PeerJ |
| Témata: | |
| On-line přístup: | https://peerj.com/articles/20377.pdf |
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