Emerging Infectious Lung Disease Monitor

The world-wide spread COVID-19 resulted in a global health care crisis. It made clear that we need the capability to detect an epidemic or pandemic disease early, that we need to be able to diagnose it rapidly, and that we require mechanisms to identify the correct treatment for individual patients. Lung imaging had an important role, shifting from an initially diagnostic- to a prognostic tool informing individual care. The project is a close interdisciplinary collaboration between experts in machine learning and radiology. It will develop new methods in the area of machine learning and image analysis to address these challenges. It will investigate and advance methods for the detection of anomalies and create techniques for the identification of newly emerging phenotypes in the patient population. This will be based on imaging data and clinical information of patients, and is challenging since it involves identifying markers that are not yet known. The second main aim is to develop models that can predict the trajectories of individual patients during their disease and recovery to guide optimal individual treatment. Here, the challenge is to learn from the real-world data collected during the early phase of a pandemic, when no treatment guidelines are available, and the observed patient histories are very diverse. The project will be embedded in international collaborations to ensure the validation of the novel methodology.