Results and News

Project Video

We are thrilled to announce the release of our project video, offering a glimpse into the world of mechanical ventilation. Learn more about how we aim to optimize invasive ventilation of critically ill patients with an AI-based decision support system.

Publications

Effects of Intraoperative higher versus lower positive end-expiratory pressure during one-lung ventilation for thoracic surgery on postoperative pulmonary complications (PROTHOR): a multi center, international, randomised, controlled, phase 3 trial

The PROTHOR Collaborative Group of the PROtective VEntilation Network (PROVE Network) for the Clinical Trial Network of the European Society of Anaesthesiology and Intensive Care. Abbenhuis, Jeroen et al. The Lancet Respiratory Medicine.

X-Vent: ICU Ventilation with Explainable Model-Based Reinforcement Learning

ECAI PAIS 2024: Farhad Safaei, Milos Nenadović, Roman Liessner, Raphael Theilen, Jakob Wittenstein, Jens Lehmann, Sahar Vahdati, ECAI 2024, Volume 392, pages 4719 – 4726, DOI: 10.3233/FAIA241069.

This study introduces a Model-Based Deep Reinforcement Learning approach to enhance the effectiveness and transparency of mechanical ventilation treatment in the critical care setting of Intensive Care Units (ICUs).

AI-Based Decision Support Systems in Intensive Care

Theilen, Raphael & Wittenstein, Jakob. (2024). AI-Based Decision Support Systems in Intensive Care. 10.3233/SSW230024.

News

All news, information on the progress of the project and events related to the IntelliLung project will be posted here. For press and media enquiries, please contact news.ekfz@tu-dresden.de.