Using physiological models and decision theory for selecting appropriate ventilator settings
Related Experiment Video
Updated: Jul 20, 2026

Ex Vivo Porcine Experimental Model for Studying and Teaching Lung Mechanics
Published on: April 19, 2024
S E Rees1, C Allerød, D Murley
1Center for Model-Based Medical Decision Support Systems, Aalborg University, Niels Jernes vej 14, 4-313, DK-9220, Aalborg East, Denmark. sr@hst.aau.dk
Objective:
To present a decision support system for optimising mechanical ventilation in patients residing in the intensive care unit.
Methods:
Mathematical models of oxygen transport, carbon dioxide transport and lung mechanics are combined with penalty functions describing clinical preference toward the goals and side-effects of mechanical ventilation in a decision theoretic approach. Penalties are quantified for risk of lung barotrauma, acidosis or alkalosis, oxygen toxicity or absorption atelectasis, and hypoxaemia.
Results:
The system is presented with an example of its use in a post-surgical patient. The mathematical models describe the patient's data, and the system suggests an optimal ventilator strategy in line with clinical practice.
Conclusions:
The system illustrates how mathematical models combined with decision theory can aid in the difficult compromises necessary when deciding on ventilator settings.
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