Prediction of mortality in sepsis patients using stacked ensemble machine learning algorithm.

Journal: Journal of postgraduate medicine

PMID: 39641373

Abstract

INTRODUCTION: Machine learning (ML) has been tried in predicting outcomes following sepsis. This study aims to identify the utility of stacked ensemble algorithm in predicting mortality.

Authors

M Babu

Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India.
M Sappani

Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India.
M Joy

Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India.
V K Chandiraseharan

Department of Medicine and Clinical Epidemiology Unit, Christian Medical College, Vellore, Tamil Nadu, India.
L Jeyaseelan

Department of Biostatistics, Mohammed Bin Rashid University of Medicine and Health Sciences, UAE.
T D Sudarsanam

Department of Medicine and Clinical Epidemiology Unit, Christian Medical College, Vellore, Tamil Nadu, India.

Keywords

Adult Aged Algorithms Area Under Curve Cohort Studies Female Hospital Mortality Humans Machine Learning Male Middle Aged Prognosis Sepsis Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (39641373)

Prediction of mortality in sepsis patients using stacked ensemble machine learning algorithm.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals