Cancer remains a leading cause of death worldwide, presenting complex challenges that demand innovative solutions. Integrating computer vision, machine learning, and AI into oncology and cancer screening can transform cancer care by enabling earlier detection, more precise prevention strategies, and personalized treatment approaches. This workshop focuses on applying multi-modal foundation models in advancing cancer research and clinical practice.Â
Multi-modal foundation models leverage diverse data modalities—such as medical imaging (radiology, histopathology), genomics, proteomics, and electronic health records (EHRs)—to create comprehensive frameworks for understanding cancer biology. Foundation models, pre-trained on large-scale datasets and fine-tuned for specific tasks, offer scalability and adaptability across different cancer types and clinical settings. Together, these approaches enable breakthroughs in early diagnosis, risk stratification, treatment optimization, and outcome prediction.
Date: Afternoon , Sunday, October 19.
Time: 13:30 - 17:30 local time
Location: 326 B
1:30 PM - 1:35 PM: Opening Remarks
1:35 PM - 2:00 PM: Foundation Models & Agentic AI that Supports Healthy Living by Daniel McDuff, Google and University of Washington
2:05 PM - 2:30 PM: Forming cellular niches - towards foundation models for single-cell and spatial omics by Anna C. Schaar, Bioptimus
2:35 PM - 3:00 PM: Foundation Model Development: How we built and Where we go next by Mingu Kang, Lunit
3:00 PM - 4:00 PM: Coffee Break
4:00 PM - 4:25 PM: Faisal Mahmood, Harvard University
4:30 PM - 4:50 PM: Oral Presentation
Medical World Model: Generative Simulation of Tumor Evolution for Treatment Planning by Yijun Yang, Hong Kong University of Science and Technology (Guangzhou)
PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology by Fatemeh Ghezloo, University of Washington and Microsoft Research
4:55 PM - 5:20 PM: Imon Banerjee, Mayo Clinic
5:20 PM - 5:30 PM: Closing Remarks
Bioptimus
Mayo Clinic - ASU
Amara Tariq, Mayo Clinic
Man Luo, Intel Labs
Ulas Bagci, Northwestern University
Chen Chen, University of Central Florida
Anthony Bilic, University of Central Florida