Making machine learning matter to clinicians: model actionability in medical decision-making

Abstract Machine learning (ML) has the potential to transform patient care and outcomes. However, there are important differences between measuring the performance of ML models in silico and usefulness at the point of care. One lens to use to evaluate models during early development is actionability...

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Autors principals: Daniel E. Ehrmann, Shalmali Joshi, Sebastian D. Goodfellow, Mjaye L. Mazwi, Danny Eytan
Format: Article
Idioma:English
Publicat: Nature Portfolio 2023-01-01
Col·lecció:npj Digital Medicine
Accés en línia:https://doi.org/10.1038/s41746-023-00753-7