Workshop on Foundation Models for Cancer: Advancing Diagnosis, Prognosis, and Treatment Response

This NIH workshop will focus on the growing role of foundation models in advancing cancer research and patient care. Attendees will learn how these sophisticated AI approaches are being applied to enhance diagnostic accuracy, predict disease outcomes, and inform treatment decisions, with discussion centered on translating research innovations into practical clinical tools and scalable technologies.

Key Topics:

• 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.

Visit the event page for more information.