A general seminar titled: AI-driven biomechanism to quantify the impact of Covid disease on breathing

Abstract: The Covid disease causes pneumonia in many patients that in the most serious cases evolves into the Acute Distress Respiratory Syndrome (ARDS), requiring assisted ventilation and intensive care. In this context, the identification of patients at high risk of developing ARDS is a key point for early clinical management, better clinical outcomes, and optimization of resources available in intensive care units. We are currently developing an AI-based computational framework that aims at predicting the ventilation efficiency of patients by using as input lung Computed Tomography (CT), the air flux in lungs obtained from biomechanical simulations, and Arterial Blood Gas analysis. By using a dual approach from AI and computer simulations we investigated the feasibility of the approach on a small clinical database of proven Covid cases where the initial CT and various reports were available. We studied the time evolution of the clinical parameters and found a correlation between the morphological information extracted from CT scans and disease outcome. Promising results illustrate the ability to predict the evolution of respiratory efficiency an aspect that would be of crucial importance for disease management.

The seminar will be held on the IAC YouTube channel CNR IAC at the link below.

Instead, the previous seminars are available at the link: Playlist Youtube IAC General Seminar 2021