Improved Interpretability Without Performance Reduction in a Sepsis Prediction Risk Score

Improved Interpretability Without Performance Reduction in a Sepsis Prediction Risk Score

<b>Objective</b>: Sepsis is a life-threatening response to infection and a major cause of hospital mortality. Machine learning (ML) models have demonstrated better sepsis prediction performance than integer risk scores but are less widely used in clinical settings, in part due to lower i...

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Bibliographic Details
Main Authors: Adam Kotter, Samir Abdelrahman, Yi-Ki Jacob Wan, Karl Madaras-Kelly, Keaton L. Morgan, Chin Fung Kelvin Kan, Guilherme Del Fiol
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Diagnostics
Subjects:
interpretability
explainability
sepsis prediction
integer risk scores
logistic regression
temporal reasoning
Online Access:https://www.mdpi.com/2075-4418/15/3/307
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