UF College of Medicine AI advances in 2025
Clinicians, researchers and students have worked together to advance patient care with AI
Oct. 6, 2025 — Artificial intelligence has yielded groundbreaking advancements in medicine, allowing clinicians, scientists and students to improve patient care, foster research and prepare for the workforce.
Several AI-related projects have seen success this year at the University of Florida College of Medicine. From creating detailed 3D maps of the brain to predicting breastfeeding challenges during pregnancy, UF Health teams continue to progress patient care and scientific discovery with AI technology, supported by UF’s HiPerGator, the fastest university-owned and operated supercomputer in the U.S.
Below are some recent AI-driven advances from the College of Medicine this year:
Scientists discover new target in potential pancreatic cancer treatment
UF Health scientists have used artificial intelligence and the HiPerGator supercomputer to uncover a new way to attack and kill pancreatic cancer cells. This discovery includes the identification of an overlooked weak spot on a protein that supercharges the lethal cancer’s growth.
Both AI and the supercomputer have enabled researchers to screen almost 140,000 compounds to find the best match to target the found vulnerability in the cancer cells.
Groundbreaking AI tool generates 3D map of the brain
UF researchers have developed a computational and AI tool that generates a high-resolution, zoomable map of the brain. The 3D map enables scientists to see the full set of molecules that produce energy for brain function.
This tool, MetaVision3D, can provide a more comprehensive understanding of metabolism in neurodegenerative disorders, including Alzheimer’s. This insight can open new avenues to the discovery of targeted treatments.
New AI model aims to increase lactation, breastfeeding rates in NICU
Clinicians and engineers at the UF College of Medicine have developed AI models that can predetermine possible challenges new mothers may encounter with breastfeeding. This allows health care teams to develop a plan to address these lactation issues even before birth.
This project, Maximizing Initiatives for Lactation Knowledge, or MILK+, has aided in the identification of mothers who are not producing enough breastmilk for premature babies in the neonatal intensive care unit.
UF Health researchers propose AI model to predict mortality in coronary artery disease patients
An AI model for predicting long-term mortality in patients with coronary artery disease was proposed by an interdisciplinary team of UF College of Pharmacy and College of Medicine researchers and their collaborators.
Published in the Journal of Biomedical Informatics, the study expands further than accurate predictions — the AI model produced by the team explores causality. With this new tool, clinicians will be able to determine the factors that contribute to the risk of patient death.
UF medical students explore artificial intelligence in research program
Over the last three years, more than 45 UF College of Medicine students have participated in the Artificial Intelligence in Medicine track of the Research and Discovery Pathways program. This program supports AI-related research projects and gives students the opportunity to build connections with research faculty, listen to guest presenters and gain access to premier tools and training.
Students in the program have conducted research in a variety of specialties, including neurosurgery and obstetrics and gynecology.
New courses explore AI’s role in improving patient safety and quality
Clinicians and scientists at the UF College of Medicine are working with AI to advance patient safety and quality improvement.
The college has launched more than a dozen free online courses, including several surrounding AI. These on-demand, fast-paced courses from the Quality and Patient Safety initiative are designed for health care professionals, students and trainees.
UF teams leverage precision medicine and AI to advance transplantation
When it comes to organ transplants, prescribing the right dose of immunosuppressants can be a challenge. Too much can lead to direct organ toxicity or to an immune system that cannot fight infections or malignancy — but too little can put a patient at risk of rejection and graft injury. Researchers are exploring the use of AI in a process called platform phenotypic personalized medicine, which would allow them to tailor an approach for each individual transplant recipient.
