Reinforcement Learning to Optimize Ventilator Settings for Patients on Invasive Mechanical Ventilation: Retrospective Study.

ABSTRACT:

Background

One of the significant changes in intensive care medicine over the past 2 decades is the acknowledgment that improper mechanical ventilation settings substantially contribute to pulmonary injury in critically ill patients. Artificial intelligence (AI) solutions can optimize mechanical ventilation settings in intensive care units (ICUs) and improve patient outcomes. Specifically, machine learning algorithms can be trained on large datasets of patient information and mechanical ventilation settings. These algorithms can then predict patient responses to different ventilation strategies and suggest personalized ventilation settings for individual patients.

Objective

In this study, we aimed to design and evaluate an AI solution that could tailor an optimal ventilator

SUBMITTER: Liu S 

PROVIDER: S-EPMC11525081 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature