A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study

Risk scores are widely used for clinical decision making and commonly generated from logistic regression models. Machine-learning-based methods may work well for identifying important predictors to create parsimonious scores, but such ‘black box’ variable selection limits interpretability, and varia...

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Detalles Bibliográficos
Autores principales: Ning, Yilin, Li, Siqi, Ong, Marcus Eng Hock, Xie, Feng, Chakraborty, Bibhas, Ting, Daniel Shu Wei, Liu, Nan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931273/
https://www.ncbi.nlm.nih.gov/pubmed/36812536
http://dx.doi.org/10.1371/journal.pdig.0000062

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931273/
https://www.ncbi.nlm.nih.gov/pubmed/36812536
http://dx.doi.org/10.1371/journal.pdig.0000062

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