Researchers are applying Artificial Intelligence to much of the research conducted in our Department of Health Outcomes and Biomedical Informatics. In the Division of Biomedical Information and Data Science, faculty members have developed expertise in electronic health records, Natural Language Processing, predictive modeling, wearable technology, and many other realms related to AI.
Students become active researchers on our AI projects. They have opportunities to work with some of the most advanced super-computing at any university. Truly the future of technology and AI is being built at the University of Florida, and our department is physically and academically located in the center of the UF experience.
Select Projects
Here are just a few examples of funded research projects with leadership from our faculty members.
Linking VA and non-VA data to Study the Risk of Suicide in Chronic Pain Patients
NIH/NIMH 1R01MH121907-01 (Patek, Bian) 08/10/2020 – 05/31/2025
The proposed project addresses this critical need by integrating large-scale VA and non-VA data to study the risk of deaths (suicide and accidental opioid overdose), and suicidal ideation and attempts in Veterans on chronic opioid therapy (COT).
Role: Co-Investigator (UF Site PI) 0.84 calendar months
Artificial Intelligence-aided Personalization on Dual Antiplatelet Therapy for Patients Underwent Coronary Stent Implantation Using Large-scale Electronic Health Records
19GPSGC35180031 (Tao) 12/01/2019 – 11/30/2023 0.24 calendar
Our goal is to develop and validate novel deep learning methods for evaluating the risk of severe adverse events (life-threatening bleeding, thrombosis, and myocardial infarction) in the postoperative period of coronary stent implantation so as to suggest personalized Dual Antiplatelet Therapy (DAPT) regimen through learning patterns from large-scale electronic health records (EHRs).
Role: Co-I (UF Site PI)
Advancing Drug Repositioning for Alzheimer’s Disease Using Real-world Data
NIH/NIA 1R56AG069880-01 (Wu, Bian, Xu, Chen) 04/01/2021 – 03/31/2023 (R56)
In this project, we propose to detect drugs that can be potentially repurposed for Alzheimer’s disease (AD) and AD-related dementias (ADRD) using 4 unique EHR data sets. The success of our study will (1) produce a drug repurposing knowledge base for AD/ADRD, (2) develop an open-source drug repurposing package, and (3) generate drug repurposing signals validated in a prospective cohort study, which will inform the design of future large-scale national trials for AD/ADRD.
Role: Principal Investigator (MPI) (Converted and recommended as a 2-year R56)
NLP to Connect Social Determinants and Clinical Factors for Outcomes Research
HOBI researchers receive PCORI® funding to connect social determinants and clinical factors for health outcomes research
PCORI ME-2018C3-14754 (Wu, Bian) 10/01/2019 – 09/30/2022
This project seeks to develop clinical natural language processing (NLP) methods and systems to extract and connect social and behavioral determinants of health (SDoH & BDoH), and adverse events (AEs) with clinical factors directly generated by clinical practice for health outcomes research. We will 1) systematically examine state-of-the-art NLP methods and develop new corpora and algorithms for SDoH, BDoH, and AEs, 2) explore automated learning methods to integrate medical knowledge with statistical NLP methods, 3) advance existing NLP methods to better handle clinical abbreviations in medical concepts, and 4) develop and disseminate an NLP package – SODA, which extracts, standardizes, and populates SDoH, BDoH, and AEs information (in addition to clinical factors) from clinical narratives
Role: Principal Investigator (Dual PI) 1.2 calendar months