DSpace: Utilizing Data Science to Predict and Improve Health Outcomes in Pediatric HIV
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Other PIs:
- Samuel Kyobe
Acronym
DSpace
Contact PI
Gaone Retshabile
View email geretshabile@gmail.comProject type
Research Project
Grant Number
U01HD114479
Summary
The project combines longitudinal electronic medical records with 'omics data to predict the development of metabolic syndrome in HIV infected children using artificial intelligence/ machine learning techniques. In addition, the project also seeks to develop more sensitive TB diagnostics biomarkers utilizing electronic health records and multi-omics data.
Other resources / documents
N/A