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Predictive Analytics for Engagement in HIV Care

Date:

March 26, 2024, 2:00 p.m. - 3:00 p.m.

Sponsor:
USC Center for AI in Society
Contact:
Hailey Winetrobe Nadel

hailey.winetrobe@usc.edu
Reservations: Cost:
Free
Details:

The USC Center for AI in Society welcomes Dr. Jessica Ridgway, Associate Professor of Medicine in the Section of Infectious Diseases and Global Health and Director of Medical Informatics at the University of Chicago and Director of Predictive Analytics for the Chicago Center for HIV Elimination, for a webinar that discusses the use of predictive analytics for engagement in HIV care. Engagement in care is essential for the health of people with HIV, but only half of people with HIV in the U.S. receive regular medical care. Dr. Ridgway will discuss her research utilizing machine learning models based on electronic medical record data to predict engagement in care among people with HIV. She has developed machine learning models using structured data as well as natural language processing of unstructured clinical notes. She will discuss challenges and pitfalls in utilizing electronic medical record data for HIV-related predictive modeling, as well as implications for implementation in clinical practice.

All are welcome.