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.
