Oct. 12, 2024
AI for All
Clinicians can better advocate for patients when they are savvy with AI.
Look to the Stars
By Strategic Communications
At the University of Pittsburgh and elsewhere, artificial intelligence is employed for drug discovery, in preventing the spread of hospital infections and in reducing the administrative burden of physicians.
“The type and scale of the education that Pitt provides will differentiate [Pitt's plan to be an AI epicenter].”
Hooman Rashidi, associate dean for AI in medicine
Anantha Shekhar, senior vice chancellor for the health sciences and John and Gertrude Petersen Dean, School of Medicine, has taken steps to ensure tomorrow’s physicians and scientists understand how AI is shaping medical care and how to best use it.
He and Liron Pantanowitz, Maud L. Menten Professor and chair of the Department of Pathology, recruited Hooman Rashidi, who has built his career around AI, to serve as Pitt School of Medicine’s associate dean for AI in medicine and make the University a world leader in AI literacy.
Rashidi, whose love for teaching comes through in any conversation with him, brings a breathless enthusiasm to Pitt’s plan to be an AI epicenter. The type and scale of the education that Pitt provides will differentiate it, he says.
Pitt’s approach to making sure its medical students are equipped for this changing landscape is rooted in a new curriculum. It started in 2024 with a series of “must know” lectures delivered by Rashidi, who also has worked with more than 40 other health care experts from across the country to create a seven-part, open-access article series on AI for Pitt and the global community. The series focuses on how AI is reshaping pathology and lab medicine.
In 2026, Rashidi will introduce a fully self-paced and interactive AI elective course called Pitt-AI-cademy—a collection of more than 25 fully interactive AI education apps. Those apps will all be under one umbrella to make it a seamless and engaging educational experience. Students will not need coding experience or a machine learning background to take the course.