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UPenn medical school names first vice dean of AI

Marylyn Ritchie will help develop a strategy for using and teaching AI at Penn's medical school.

Marylyn Ritchie has been named the inaugural vice dean of artificial intelligence and computing at University of Pennsylvania's Perelman School of Medicine
Marylyn Ritchie has been named the inaugural vice dean of artificial intelligence and computing at University of Pennsylvania's Perelman School of MedicineRead moreDaniel Burke Photography

University of Pennsylvania wants to establish a strategy for using and teaching artificial intelligence, as the technology becomes more common in medicine and everyday life.

The Perelman School of Medicine named Marylyn Ritchie the first vice dean of artificial intelligence and computing. Ritchie, who also works as the director of Penn’s Institute for Biomedical Informatics, will be responsible for developing a plan to incorporate AI into medical school education.

Mitchell Schnall, Penn’s former chief of radiology, has been named the first senior vice president for data and technology solutions at University of Pennsylvania Health System. He will work to expand AI’s use across Penn Medicine’s hospitals and physician groups.

AI tools — such as the popular chatbot ChatGPT, which can draft resumes and write computer code — are increasingly popular and accessible. But these tools also make mistakes, and must be used carefully in medicine.

The health system and medical school want to establish a cohesive approach to using AI and establish best practices for vetting new AI tools.

“We know AI is becoming part of the fabric of society and likely to be there in clinical care,” Ritchie said. “It’s really important that providers can use it to their advantage.”

» READ MORE: Lab tests and scans interpreted by AI? These Penn doctors are researching the good — and bad — ways to use AI in health care

AI in medical school

Ritchie will oversee a committee tasked with making recommendations for how to incorporate AI into Penn’s medical training programs.

Doctors-in-training need to learn what AI is good for — and what it’s not good for, Ritchie said. She wants medical students to learn how to be skeptical of new AI tools and gauge whether they will be useful.

She will also help decide which medical research specialties are most promising for Penn’s investment in AI.

For instance, Ritchie sees potential for Penn to advance AI research in immune health.

Ritchie thinks researchers could use AI to analyze the health records of patients with autoimmune diseases to find patterns, such as common lab results or secondary illnesses. The information could help doctors predict patients at risk for developing an autoimmune disease.

Scaling AI tools across Penn Medicine

AI is already being used in some parts of Penn.

Every Cure, a nonprofit organization co-founded by a Penn immunologist, uses AI to identify existing medications that could be used to treat rare diseases, for which there are few or no treatment options.

Radiologists use AI tools to help search for abnormalities in CT scans and other imaging tests.

» READ MORE: This UPenn doctor’s experience with a rare disease motivated him to use AI to find new treatments for others

Schnall will help identify the AI tools with the greatest potential and ways to scale them across the health system.

For instance, Schnall is interested in exploring how AI could help doctors more quickly digest patients’ medical history.

Electronic medical records are troves of information, but they’re poorly organized. Doctors may spend hours combing through a patient’s past test results and doctors’ notes for clues about their current condition.

An AI tool might be able to read patient records and create what Schnall called a “clinical context,” a summary or digest of the patient’s medical history that’s easier to search.

“There’s going to be a huge impact on the way we practice medicine,” Schnall said.