354P A multimodal deep learning model for prediction of early progression in patients with advanced hepatocellular carcinoma treated with atezolizumab-bevacizumab
- Authors: Celsa, C.; Contino, S.; Cannella, R.; Ciccia, R.; Crescimanno, G.; Cruciata, L.; Restuccia, S.; Giusino, G.; Calascibetta, S.; Cusimano, G.; Quartararo, A.; Cabibbo, G.; Cirrincione, G.; Pirrone, R.; Cammà , C.
- Publication year: 2025
- Type: Abstract in atti di convegno pubblicato in volume
- OA Link: http://hdl.handle.net/10447/695220
Abstract
Atezolizumab-Bevacizumab is recommended as first-line treatment for advanced/unresectable hepatocellular carcinoma (HCC). However, validated clinical or radiological systems able to predict early treatment response or identify non- responsive patients at risk of early therapeutic failure are currently lacking. We developed a multimodal AI model to predict 6-month progression-free survival (PFS)