AI-powered model improves prediction of bladder cancer treatment outcomes
9 Articles
9 Articles


AI meets oncology: New model personalizes bladder cancer treatment
Leveraging the power of AI and machine learning technologies, researchers developed a more effective model for predicting how patients with muscle-invasive bladder cancer will respond to chemotherapy. The model harnesses whole-slide tumor imaging data and gene expression analyses in a way that outperforms previous models using a single data type.
Predicting response to neoadjuvant chemotherapy in muscle-invasive bladder cancer via interpretable multimodal deep learning
Building accurate prediction models and identifying predictive biomarkers for treatment response in Muscle-Invasive Bladder Cancer (MIBC) are essential for improving patient survival but remain challenging due to tumor heterogeneity, despite numerous related studies. To address this unmet need, we developed an interpretable Graph-based Multimodal Late Fusion (GMLF) deep learning framework. Integrating histopathology and cell type data from stand…
AI-powered model improves prediction of bladder cancer treatment outcomes
Leveraging the power of AI and machine learning technologies, researchers at Weill Cornell Medicine developed a more effective model for predicting how patients with muscle-invasive bladder cancer will respond to chemotherapy.
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