Predicting Hypoxia Using Machine Learning: Systematic Review.

ABSTRACT:

Background

Hypoxia is an important risk factor and indicator for the declining health of inpatients. Predicting future hypoxic events using machine learning is a prospective area of study to facilitate time-critical interventions to counter patient health deterioration.

Objective

This systematic review aims to summarize and compare previous efforts to predict hypoxic events in the hospital setting using machine learning with respect to their methodology, predictive performance, and assessed population.

Methods

A systematic literature search was performed using Web of Science, Ovid with Embase and MEDLINE, and Google Scholar. Studies that investigated hypoxia or hypoxemia of hospitalized patients using machine learning models were considered. Risk of bias was assessed

SUBMITTER: Pigat L 

PROVIDER: S-EPMC10879670 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature