A new study published in npj Digital Medicine highlights the potential of an interpretable deep learning framework to improve the prediction of responses to neoadjuvant chemotherapy (NAC) in patients with muscle-invasive bladder cancer (MIBC). The Graph-based Multimodal Late Fusion (GMLF) model, integrates histopathological images and gene expression data to predict treatment outcomes and identify key biomarkers.

A new study published in npj Digital Medicine highlights the potential of an interpretable deep learning framework to improve the prediction of responses to neoadjuvant chemotherapy (NAC) in patients with muscle-invasive bladder cancer (MIBC).

Stockholm, Sweden – In a groundbreaking study, researchers from the Karolinska Institute, led by Professor Elisabeth Epstein, have developed an AI-driven ultrasound image analysis model that demonstrates exceptional performance in detecting ovarian cancer. Published in Nature Medicine...