Machine Learning-Based Early Prediction of Sepsis Using Electronic Health Records: A Systematic Review.

ABSTRACT:

Background

Sepsis, a life-threatening infection-induced inflammatory condition, has significant global health impacts. Timely detection is crucial for improving patient outcomes as sepsis can rapidly progress to severe forms. The application of machine learning (ML) and deep learning (DL) to predict sepsis using electronic health records (EHRs) has gained considerable attention for timely intervention.

Methods

PubMed, IEEE Xplore, Google Scholar, and Scopus were searched for relevant studies. All studies that used ML/DL to detect or early-predict the onset of sepsis in the adult population using EHRs were considered. Data were extracted and analyzed from all studies that met the criteria and were also evaluated for their quality.

Results

This systematic review examine

SUBMITTER: Islam KR 

PROVIDER: S-EPMC10488449 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature