The UF Health AI community includes researchers developing, evaluating and implementing health-related AI applications, as well as methodological and computational experts developing new AI methods. This page spotlights teams in the news, college highlights and a sampling of recent publications involving UF Health faculty.
Around the Colleges
College of Dentistry faculty are using AI to find patterns of gene expression of oral diseases and link imaging, pathology and genomic data to improve patient outcomes. Dentistry researchers are also using machine learning methods to understand the neurobiological contributors of pain in older adults.
College of Medicine teams are harnessing AI on many fronts. Clinician-scientists are developing AI-enabled systems to guide perioperative and acute care decision-making, such as pervasive sensing and remote monitoring to diagnose and treat complex conditions in the ICU. Data scientists are working to solve big data problems to spur data-driven medicine, and basic scientists are advancing AI-enhanced methods for analyzing molecular data.
College of Nursing researchers have in-depth knowledge and experience in capturing, transforming and analyzing structured and unstructured nursing and patient data from electronic health records, and in leveraging national data networks for nursing science and AI applications. A leader in nursing informatics research, the College of Nursing is poised to advance AI initiatives by strengthening seven areas.
College of Pharmacy researchers are using AI tools to address the nation’s health care challenges, from developing new cancer drugs to stemming the opioid epidemic. AI is transforming the way we approach drug discovery, design clinical trials, personalize treatments and make medications safer.
College of Public Health and Health Professions researchers are using AI tools to improve population health and treatment interventions. Research themes include applied AI to tackle real-world health issues, ethical AI to develop fair and equitable models, and interdisciplinary AI to develop new methods.
College of Veterinary Medicine experts are exploring the use of machine-learning techniques to improve diagnostic accuracy and prediction, predict the risk of infectious diseases in livestock and aquatic species, and reduce the use of antimicrobials in livestock. Faculty also are collaborating with engineering colleagues to use single cell transcriptomics for oncology research.
In the Literature
Below is a sampling of recent AI-related publications involving authors affiliated with the UF health colleges. Organized by the UF Health AI initiative areas of focus, articles encompass a mix of AI methods and applications, and they highlight influential research articles, literature reviews and expert commentary and other scholarly contributions. Authors span a total of 10 UF colleges, three UF campuses, and numerous partner institutions.
In the News
With trial and error, repetition and praise, when a puppy hears “Sit!” they learn what they’re expected to do. That’s reinforcement learning, and it’s a…
In the latest development in precision medicine approaches to treating pediatric leukemia, UF Health researchers have developed a genetic score to predict…
A project led by a researcher in the University of Florida’s College of Public Health and Health Professions seeks to improve the effectiveness of clinical…
With $1 million in support from University of Florida President Ben Sasse’s strategic funding initiative, investigators at the Evelyn F. and William L.…