Medical diagnosis often is based on information visible from medical images. But what if machine learning and artificial intelligence could help our doctors gain more knowledge from medical images and therefore predict diseases earlier? New research indicates this is indeed possible, and the implications for preventive medicine and several disease types are large. Learn about it in this talk.
Shinjini graduated from high school at age 16, earned a PhD at 25, and was named one of Pittsburgh’s 40 under 40 in 2016. In her PhD work at Stanford, Shinjini employed machine learning that trained computers to detect patterns in medical images. That technology enables doctors to detect osteoarthritis three years before symptoms are evident. Shinjini is currently an MD-PhD scientist in the Medical Scientist Training Program (MSTP), a collaboration between the University of Pittsburgh and Carnegie Mellon University. Her research focuses on medical diagnosis in the pre-disease stage when a patient is still asymptomatic. She is also an advocate for women and minorities in STEM professions.
This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx