Yiyang Liu,

I see myself as an epidemiologist and data scientist specializing in HIV and substance use research. I have rich experience working with OneFlorida+ (OneFL) electronic health records (EHR) and contributed to several HIV-related projects using OneFL EHRs. In one of my first-authored papers, I have developed and validated a rule-based HIV computable phenotype algorithm that leverages the multi-domain structured electronic health record (EHR) data and has identified over 70k patients with confirmed HIV diagnoses. Building on this virtual HIV cohort, I have been awarded an industry fund as a primary investigator (PI) to examine long-acting HIV antiretroviral therapy uptake among people with HIV. Additionally, I have participated as a co-investigator on a UF Clinical and Translational Science Institute (CTSI) pilot grant and led efforts in one of the aims to identify and characterize PrEP users using OneFL EHRs. I am currently preparing an R34 grant aiming to build an EHR-based HIV prediction model to better identify patients who might benefit from PrEP, especially among women.

• Great Teaching for New Faculty Certificate

  UF Center for Teaching Excellence

0000-0002-5519-3853

• Alcohol and substance use
• HIV
• HIV Prevention
• Mental Health
• data science
• electronic health records