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AI in Oncology: Predicting Cancer’s Course Frontiers in Medicine 2024 Imagine how treatment for cancer could be individualized if we could accurately predict each patient’s unique disease trajectory. Dr. Plevritis leads a cancer systems biology lab that is pioneering the new field of spatial biology to do just that. By combining tailored AI models with many types of data from patient samples, her team is able to watch the story of health unfold over time. She hopes to predict with enhanced accuracy which clinical event will likely be next for cancer patients based on their medical and molecular history—knowledge that can guide advances in early detection and treatment response. Sylvia Plevritis, PhD Chair, Department of Biomedical Data Science William M. Hume Professor, School of Medicine Professor, Biomedical Data Science and Radiology Part of Frontiers in Medicine, Stanford Medicine's premier annual event that showcases pioneering breakthroughs in the most promising fields in biosciences and medicine presented by world-class Stanford faculty. Please visit frontiersinmedicine.stanford.edu to learn more.