Explainable machine learning to predict long-term mortality in critically ill ventilated patients: a retrospective study in central Taiwan

Explainable machine learning to predict long-term mortality in critically ill ventilated patients: a retrospective study in central Taiwan

Abstract Background Machine learning (ML) model is increasingly used to predict short-term outcome in critically ill patients, but the study for long-term outcome is sparse. We used explainable ML approach to establish 30-day, 90-day and 1-year mortality prediction model in critically ill ventilated...

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Bibliographic Details
Main Authors: Ming-Cheng Chan, Kai-Chih Pai, Shao-An Su, Min-Shian Wang, Chieh-Liang Wu, Wen-Cheng Chao
Format: Article
Language:English
Published: BMC 2022-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Mortality prediction
Critical illness
Mechanical ventilation
Machine learning
Interpretability
Online Access:https://doi.org/10.1186/s12911-022-01817-6

Internet

https://doi.org/10.1186/s12911-022-01817-6

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