Reinforcement Learning to Optimize Ventilator Settings for Patients on Invasive Mechanical Ventilation: A Retrospective Study (Preprint)

One of the significant changes in intensive care medicine over the past two decades is the acknowledgement that improper mechanical ventilation settings substantially contribute to pulmonary injury in critically ill patients. Artificial intelligence (AI) solutions can be used to optimize mechanical ventilation settings in intensive care units (ICUs) and to 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.