PREDICT
L’Ente Capofila del progetto è IRCCS Istituto Europeo di Oncologia. Il Responsabile Scientifico del progetto è la Professoressa Elena De Momi.
| Patologia: | Tumore Ovarico |
| Area Tematica: | Intelligenza Artificiale |
| Data di Inizio Progetto: | 01.02.2026 |
| Data di Fine Progetto: | 31.01.2029 |
| Finanziamento: | € 1.800.000,00 |
| Partenariato | IRCCS Istituto Europeo di Oncologia Università degli Studi dell’Insubria Politecnico di Milano |
ABSTRACT
The PREDICT project aims to advance Ovarian Cancer (OC) treatment by developing generative Artificial Intelligence (AI) models to predict tumor progression and chemotherapy response using diagnostic Computed Tomography (CT) scans. OC is characterized by aggressive progression, high relapse rates, and unpredictable treatment responses, posing significant challenges in patient care.
To address these challenges, the project will generate synthetic CT scans that simulate post-chemotherapy outcomes, allowing clinicians to make earlier, personalized treatment decisions. This approach could reduce unnecessary surgeries, optimize chemotherapy regimens, and improve both patient outcomes and healthcare efficiency.
Our study builds on the foundations of the Under-XAI project (PNRR-MAD-2022-12376574), leveraging findings and established collaborations to accelerate progress in development. A large, multi-center dataset integrating clinical and imaging data will be created to ensure both accuracy and comprehensive representation. Advanced generative AI models will be developed to simulate tumor evolution after chemotherapy, with a strong emphasis on validating their clinical utility within diagnostic workflows. This research aims to generate robust evidence for overcoming barriers to the integration of AI into medical practice.
By bridging clinical practice with advanced AI research, PREDICT enhances decision-making and delivers more personalized, effective care for OC patients.