June 6, 2025 — When University of Florida medical student Taylor Edwards began her studies three years ago, she thought it would be interesting to embrace something groundbreaking in the field.

“I knew how many AI resources the university had at hand, and I identified a big knowledge gap there for myself,” Edwards said. “So, I wanted to get involved.”

Edwards joins more than 45 UF College of Medicine students who have participated in the Artificial Intelligence in Medicine track of the Research and Discovery Pathways Program over the last three years. The pathway enables UF medical students to conduct AI-related research projects, build connections with research faculty, hear presentations from guest presenters and gain access to premier tools and trainings.

Medical students in the program have conducted AI-aided research in specialties ranging from obstetrics and gynecology to neurosurgery.

Edwards can often be found at the Norman Fixel Institute for Neurological Diseases at UF Health, where she collaborates with Joshua Wong, M.D., an assistant professor in the Department of Neurology. Using data from patients and brain scans taken before and during surgery, their team is developing predictive algorithms to determine how much a person’s brain shifts during deep brain stimulation surgery. This is an important factor, Edwards explained, in organizing patients into risk categories that can predict how much air gets past the brain’s protective outer layer that is punctured during surgery. 

“I’m on my neurology rotation right now,” she said. “It’s my first one, and we’ve gotten to see some patients who have benefited from deep brain stimulation surgeries. It’s really cool to be on the other side now and see positive outcomes.”

Edwards presented her research at the Medical Student Research Symposium, where she was named a semi-finalist. She is also looking into external conferences to present her findings.

Another project from the Artificial Intelligence in Medicine track of the Research and Discovery Pathways Program, a collaboration among medical students in the program, explored how students nationwide are using AI tools such as ChatGPT to enhance their medical education.

“Unsurprisingly, we found students with a stronger baseline understanding of AI were more likely to use the tool conscientiously,” said third-year medical student Alan Xu. “This supports the growing belief that structured AI education may be essential to prepare future physicians to use these tools responsibly and effectively.”

As part of the track, students gain additional AI education by also getting the chance to explore facilities like UF’s new Malachowsky Hall for Data Science and Information Technology and access trainings from companies like NVIDIA and tools like UF’s state-of-the-art supercomputer, HiPerGator.

“We’re going to medical school to learn all the medical knowledge, and AI is the pinnacle of technology, so it was cool to see that UF has a way to combine the two,” said third-year medical student Justin Daniels. “What got me interested in the AI pathway was being able to fine tune both sets of skills.”

Daniels has worked on two AI research projects as part of the track. First, he worked with Matthew Decker, M.D., M.P.H., an assistant professor in the Lillian S. Wells Department of Neurosurgery, where he helped develop a 3D convolutional neural network — an algorithm primarily used for processing visual data like images and videos — utilizing UF’s HiPerGator supercomputer. The neural network was developed to analyze patient imaging and chart data to accurately predict the need for future surgical intervention.

He also worked with associate professor Cameron Smith, M.D., Ph.D., and assistant professor Meghan Brennan, M.D., M.S., from the Department of Anesthesiology on a project to develop an AI tool to accurately label organs and predict if a stomach is empty during an abdominal ultrasound.

“If we used this in the future, it would help determine whether there needed to be solid aspiration risk protocols in place,” he said.

Brennan, who is part of the faculty team for the AI research pathway and clinical director of research for the Division of Critical Care Medicine, said that by medical students immersing themselves in AI-related projects during their training, they are preparing to enter the modern medical workforce.

“Using AI effectively will help us better care for our patients,” she said. “Just like any other tool, we can use it to be more productive clinicians.”