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

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, which i...

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Detalles Bibliográficos
Autores principales: Ehrmann, Daniel E., Joshi, Shalmali, Goodfellow, Sebastian D., Mazwi, Mjaye L., Eytan, Danny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Perspective
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871014/
https://www.ncbi.nlm.nih.gov/pubmed/36690689
http://dx.doi.org/10.1038/s41746-023-00753-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871014/
https://www.ncbi.nlm.nih.gov/pubmed/36690689
http://dx.doi.org/10.1038/s41746-023-00753-7

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