Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach
Journal
Journal of medical Internet research
Journal Volume
24
Journal Issue
4
Date Issued
2022
Author(s)
Park, James Yeongjun
Hsu, Tzu-Chun
Hu, Jiun-Ruey
Chen, Chun-Yuan
Hsu, Wan-Ting
Lee, Matthew
Ho, Joshua
Abstract
Although machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to predict sepsis mortality in an administrative database. Therefore, we examined the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compared it with that of the conventional context knowledge-based logistic regression approach.
Subjects
SuperLearner; machine learning; mortality; sepsis
Publisher
JMIR PUBLICATIONS, INC
Type
journal article