Multi-Modal Foundation Models for Cancer Detection and Prevention

This workshop explores how multi-modal foundation models can revolutionize cancer care by integrating AI, computer vision, and machine learning. By leveraging diverse data types—such as medical imaging, genomics, and EHRs—these models enable earlier detection, personalized treatment, and better outcome prediction. Pre-trained on large datasets and fine-tuned for specific tasks, they offer adaptability across cancer types and clinical settings. The event brings together experts from academia, industry, and healthcare to share research, tackle challenges in data integration and model interpretability, and promote clinical translation. The goal is to advance cancer research and accelerate the real-world impact of AI in oncology.