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...
Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2022-06-01
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Series: | PLOS Digital Health |
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931273/?tool=EBI |