By Manny Rea
This year, six UF College of Medicine medical students were granted a unique funding opportunity: the Oberndorf AI Catalyst Grant Endowment. Supported by a generous gift from Lou and Rosemary Oberndorf, the fund empowers these students to develop leading-edge, artificial intelligence-based projects that address challenges and unlock opportunities in patient care, diagnostics, research, or health care management. Recipients work on forward-thinking projects while receiving hands-on research training and mentorship from leading scientists from the College of Medicine and Herbert Wertheim College of Engineering.
Originally announced at the 13th Annual Celebration of Research in 2023, and first awarded in 2024, the Oberndorf AI Catalyst Grant Endowment is the College of Medicine’s first AI-focused award. Longtime supporters of education, the Oberndorf family’s generosity to UF dates back to the ’90s, most notably with a previous gift in 2016 to establish the Louis H. Oberndorf Experiential Learning Theatre in the George T. Harrell, M.D., Medical Education Building. After being inspired by medical students’ enthusiasm to use AI’s power to accelerate medicine, Lou Oberndorf established the family’s latest endowment.
UF college of medicine office of research
Oberndorf AI Catalyst Grant Endowment Fund
The fund empowers students to develop leading-edge, artificial intelligence-based projects that address challenges and unlock opportunities in patient care, diagnostics, research, or health care management.
For the Catalyst Grant’s inaugural year, the Intelligent Clinical Care Center and the College of Medicine Office of Research welcomed proposals from second-, third-, and fourth-year medical students working on AI-based team research projects. They awarded six recipients $5,000 plus travel funds to present team findings at a medical conference.
Danielle Snyder is one of the six making significant strides in her research. A third-year medical student interested in an obstetrics and gynecology career, Snyder created her project, “Precision in Prediction: Harnessing Machine Learning for an Innovative Endometriosis Prediction Model,” in response to a lack of noninvasive diagnostic tools for the condition, which affects about 190 million women of reproductive age globally.
“We already know endometriosis presents so variably, and without a reliable tool it can take years before women receive a proper diagnosis and treatment,” Snyder said.
Snyder and her team collected varied medical information such as patient histories, physical exams, imaging findings, and pathology results to discern which health factors would be predictive of endometriosis. Realizing that the myriad data from more than 800 patients required high-level data analysis, the team decided to capitalize on the power of AI.
“Bringing AI in to help understand exactly which presenting factors are associated with a diagnosis of endometriosis will hopefully allow primary care providers to diagnose endometriosis with a similar accuracy to specialists in the field,” she said.
The team had already spent eight months collecting patient data before learning about the Catalyst Grant, which offered a chance to fund the AI model creation and implementation portion of the research. Earning the grant allowed them to expand their team to include mentor François Modave, Ph.D., a professor of artificial intelligence in the department of anesthesiology, as well as additional medical and Ph.D. students who helped develop the prediction model.
Snyder is now working to implement the model in the UF Health Minimally Invasive Gynecological Surgery Center of Excellence, a clinic that performs gynecologic surgeries with significantly less blood loss, scarring, postoperative pain, and faster recovery than traditional surgery. Surgeons in the clinic will triage patients with suspected endometriosis and update the model with new data to further improve accuracy.
Snyder and her team plan to present their findings at the American Association of Gynecologic Laparoscopists annual conference in November and are working on a manuscript to submit to The New England Journal of Medicine — all possible thanks to the grant and the generosity of the Oberndorfs.
Alongside Snyder, five other students received the Oberndorf AI Catalyst Grant. We checked in with these projects to learn more about their research goals:
