Development and evaluation of a reinforcement learning-based decision support system for mechanical ventilation in acute respiratory failure

Abstract

This data publication contains development (Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Local Ethical Committee Approval: BO-EK-423082021) and external validation data set (extracted and preprocessed from MIMIC-IV) for the developed first version of the IntelliLung-AI algorithm based on Reinforcement Learning. Data holds the input/output of the training, testing (development), as well as external validation pipeline as published in the GitLab repository (https://github.com/NIMI-research/rl-acute-respiratory-failure-dss).