Abstract

This study provides and overview of data system and linkage process for people living with HIV in South Carolina. The purpose of the study is developing and identifying best machine-learning based predictive model for HIV medical treatment status using historical data for a comprehensive established data repository. We provide findings from the study thus far.

Bio

Banky Olatosi is tenure track assistant professor in the Department of Health Services Policy and Management, at the Arnold School of Public Health, University of South Carolina (UofSC). He is published in peer-reviewed journals and his research interests are in the fields of Big Data Health Analytics, HIV/AIDS, COVID-19 and rural health. He has expertise in the field of Data Analytics and Data Mining, and currently has NIH grant funding in this area. He co-leads the UofSC national big data health science center (BDHSC). He is a Fellow of the American College of Healthcare Executives (FACHE). He is passionate and committed to the improvement of graduate healthcare education. He currently serves as the Chair of the CAHME Accreditation Council and is also a CAHME national board member. He is a UofSC 2021 Breakthrough Research award winner. Banky Olatosi earned his doctorate in Health Services Policy and Management from the University of South Carolina and earned his MPH in Public Health Administration and Policy from the University of Minnesota (Twin Cities). He also holds a master’s degree in biochemistry from the University of Lagos.

Location

In person

Swearingen Engineering Center in Room 2A31

Virtual MS Teams

Time

2:20-3:10pm