About
We are the BEAR group (Biomedicine, Engineering & AI Research) at the Department of Information Engineering and Computer Science (DISI), University of Trento. We plan, design and develop AI-based clinical decision support systems.
Our goal is to reduce diagnostic delays, doctors’ workload and the risk of cognitive biases, and to increase diagnostic accuracy, access to care and support in complex decisions. In practice, this means standardizing image interpretation, reducing variability between diagnoses, making sure critical findings are consistently reported, and building the foundation for personalized therapeutic strategies and more targeted patient management.
Research
Five research lines in medical imaging, from methods to clinical impact. Each one comes with open MSc thesis topics.
Combining complementary imaging modalities, clinical and biological data into robust and interpretable models, even when some acquisitions are missing or corrupted.
Related theses
Generating anatomically plausible medical images conditioned on disease and treatment, to augment data and simulate clinical scenarios.
Related theses
Forecasting how a disease evolves from longitudinal scans and combining diagnosis with prognostic prediction for personalized care.
Related theses
Systems that recognise low-quality inputs and uncertain cases, and that explain their outputs with reports grounded in visual evidence.
Related theses
Detection, segmentation, classification, characterization and report generation from volumetric imaging data, learned together in a single model.
Related theses
Clinical partners
News
Join us
We are always happy to hear from motivated people interested in AI for medicine: open positions, spontaneous applications for PhD and postdoc roles, MSc thesis projects for UniTn students, visiting researchers and clinical collaborations with hospitals and companies.