Foundation Models for Cancer: Advancing Diagnosis, Prognosis, and Treatment Response
March 24 – March 26, 2026
Join DCTD for this virtual workshop to explore how foundation models—a powerful class of advanced AI models—can transform cancer research and clinical care. We will focus on the models’ potential to improve diagnosis, prognosis, and treatment response, with a strong emphasis on clinical translation and technology development. Registration is open now for all interested attendees!
- Foundation Model Primer: A high-level introduction to foundation models. Multimodal Data: Combining pathology, radiology, omics, and patient data into unified models.
- Prediction: Predicting therapeutic response, resistance, and patient outcomes
- Validation and Reproducibility: Ensuring model results are consistent and reliable for real-world clinical performance and use.
- Diagnostic Case Studies: Real-world applications for early detection and automated diagnostics.
- Federated Learning: Approaches to training robust models across multiple institutions—without sharing sensitive patient data.
- Challenges, Risk, and Regulation: Addressing model interpretability and regulatory considerations for clinical adoption.
Additional information and updates can be found on the event site here.