An explainable predictive machine learning model of gangrenous cholecystitis based on clinical data: a retrospective single center study

An explainable predictive machine learning model of gangrenous cholecystitis based on clinical data: a retrospective single center study

Abstract Background Gangrenous cholecystitis (GC) is a serious clinical condition associated with high morbidity and mortality rates. Machine learning (ML) has significant potential in addressing the diverse characteristics of real data. We aim to develop an explainable and cost-effective predictive...

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Bibliographic Details
Main Authors: Ying Ma, Man Luo, Guoxin Guan, Xingming Liu, Xingye Cui, Fuwen Luo
Format: Article
Language:English
Published: BMC 2025-01-01
Series:World Journal of Emergency Surgery
Subjects:
Gangrenous cholecystitis
Machine learning
Integrated learning
Data imbalance
Diagnostic predictive model
Online Access:https://doi.org/10.1186/s13017-024-00571-6
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https://doi.org/10.1186/s13017-024-00571-6

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