artificial intelligence for the public’s health

Researchers in the College of Public Health and Health Professions are using artificial intelligence tools to improve population health and treatment interventions.

research themes

Applied AI

Studies led by faculty in both public health and health professions disciplines explore real-world health issues, including the outcomes of pharmaceutical treatments in large populations, the effects of re-purposing drugs for other health conditions, the impact of environmental contaminants on the risk of diseases, such as cancer, and the use of assistive technology to improve daily life for older adults and people with disabilities.

Ethical AI

Scientists are developing fair and equitable models that not only recognize social bias and health disparity, but also can be acted upon in interventions. Examples include increasing access to care for vulnerable and underserved populations and reducing stigma in order to improve quality of life for people living with HIV.

Interdisciplinary AI

Research across disciplines includes fusing molecular epidemiology and deep learning methods to track and curb transmission of infectious diseases, as well as AI-empowered neurocognitive research.  

Methodological AI

Methodological approaches include advancements in machine learning and “causal AI” with strong biostatistical foundations, such as efficient multi-omics big data analysis, deep propensity networks, automated learning of causal effects from large-scale electronic health records, multi-site large clinical trials, and Bayesian dynamic trials.

new hires

Aprinda Indahlastari, Ph.D.

Dr. Indahlastari currently serves as a research assistant professor of clinical and health psychology. Her broader research interests are in optimizing and personalizing existing medical devices through the use of computational modeling, such as machine learning and finite element methods, with the goal of achieving precision medicine that is tailored to each person.

Indahlastari, Aprinda

Muxuan Liang, Ph.D.

Dr. Liang will join the department of biostatistics from the Fred Hutchinson Cancer Research Center. In his research, he applies statistical and machine learning techniques to large databases like electronic health records, to help health care providers make decisions based on patient-level information. These may include decisions about treatment, tailored cancer surveillance strategy and individualized risk prediction.

Liang, Muxuan

Zhoumeng Lin, BMed, PhD, DABT, CPH

As an associate professor in the department of environmental and global health, Dr. Lin’s research focuses on the development and application of computational technologies to address research questions related to nanomedicine, animal-derived food safety assessment, and environmental chemical risk assessment. The long-term goal is to develop AI-assisted computational approaches to support decision-making in human, animal and environmental health.

Zhoumeng Lin

Feifei Xiao, Ph.D.

A member of the department of biostatistics, Dr. Xiao focuses on the development and application of powerful and efficient statistical methods for high throughput genetics and genomics data. Her work includes ongoing projects in cancer, aging and other public health related outcomes, with the goal of providing efficient statistical tools to integrate genetic and genomic data into the practice of precision medicine.

Feifei Xiao

Panayiotis (Takis) Benos, Ph.D.

Dr. Benos will join the department of epidemiology from the University of Pittsburgh. His group works on the intersection of machine learning, computational biology and systems medicine. The ultimate goal of the group is to identify risk factors and mechanisms affecting aging and contributing to the onset and progression of chronic diseases and cancer. They develop and use probabilistic graphical models and other machine learning methods to integrate and mine high-dimensional, multi-modal biomedical data and to investigate biological processes pertinent to health and disease. The disease focus of the lab includes chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, cardiovascular diseases and alcoholic hepatitis. Other ongoing projects are related to the identification of microbiome contributions to clinical outcomes in critically ill patients and the understanding of the mechanisms of cancer immunoprevention.

Takis Benos headshot

Noah Hammarlund, Ph.D.

Dr. Hammarlund joins the department of health services research, management and policy from the University of Washington. In his research, he merges health economics with innovations in artificial intelligence to investigate the role of social factors in the delivery of healthcare with the goal to better target policy solutions to disparities in health.  

Hammarlund, Noah

Featured projects

Predicting HIV transmission patterns

Dr. Mattia Prosperi and colleagues are using an AI technique known as deep learning to study patterns of HIV transmission. Deep learning methods use artificial neural networks that learn from complex data sets. The researchers plan to identify social, demographic and behavioral risk profiles that will enable more powerful predictions about future trends, including where HIV transmission clusters are likely to occur.

red ribbon

Preventing dementia

Dr. Adam Woods studies the use of non-invasive transcranial direct current stimulation for improving brain health among older adults. With support from a new grant, Woods and his team are using neuroimaging-derived computational modeling and artificial intelligence-based machine learning methods to better understand the mechanisms of treatment response and to develop precise individualized models for dosing.

Adam Woods with older adult

education

Undergraduate

The college has created three new undergraduate courses that can be taken as part of UF’s campus-wide certificate program, AI Fundamentals and Applications, or as part of a PHHP-specific certificate program that will be submitted to the UF Curriculum Committee in Fall 2021. The three courses are “Higher Thinking for Healthy Humans: AI in Healthcare and Public Health,” “Ethics in AI: Who’s Protecting Our Health” and “Data Visualization in the Health Sciences.”

Graduate

The college has begun developing a certificate in Artificial Intelligence Research Methodologies in Healthcare and Public Health for graduate students that will focus on using AI to answer health-related research questions. Once these are fully established, the courses will be developed and submitted to the Graduate Council for approval.

AI NEWS

UF team receives $6.6 million to study treatments…

Researchers will evaluate three promising treatments designed to improve brain health in people with HIV who consume alcohol.

3d rendering of human brain on technology background

AI and your health

Researchers are using artificial intelligence technology to improve treatment outcomes and population health.

PT doing therapy

Study shows artificial intelligence’s potential…

AI, combined with MRI scans of the brain, may be able to predict whether people with early memory loss will go on to develop dementia or…

Dr. Joseph Gullett pointing to brain scans on computer screen

Researchers use AI to develop tool for predicting…

Researchers led by Dr. Zhoumeng Lin are building a tool that can offer drug researchers insight into how well a new nanoparticle-based cancer therapy…

more information

Contact

For more information on AI activities at PHHP, contact the college’s coordinator for AI, Dr. Mattia Prosperi.

Diversity, Equity and Inclusion

The college is committed to creating an inclusive environment where everyone is respected and valued.

AI at UF Health

UF Health is creating an academic hub to advance AI in the health sciences grounded in the values of community, trustworthiness, and diversity, equity and inclusion.

AI AT The university of florida

AI leadership for the future

The university is becoming a worldwide leader in AI workforce development with an AI-across-the-curriculum approach that infuses AI and data science into all academic endeavors. UF’s $100 million investment in AI will transform Florida’s workforce and economy to resonate globally and continue the university’s rise into America’s top-tier public universities.

Century Tower