Machine learning with routine electronic medical record data to identify people at high risk of disengagement from HIV care in Tanzania

Machine learning with routine electronic medical record data to identify people at high risk of disengagement from HIV care in Tanzania

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Machine learning methods for health care delivery optimization have the potential to improve retention in HIV care, a critical target of global efforts to end the epidemic. However, these methods have not been widely applied to medical record data in low- and middle-income countries. We used an ense...

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Bibliographic Details
Main Authors: Carolyn A. Fahey, Linqing Wei, Prosper F. Njau, Siraji Shabani, Sylvester Kwilasa, Werner Maokola, Laura Packel, Zeyu Zheng, Jingshen Wang, Sandra I. McCoy
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLOS Global Public Health
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021592/?tool=EBI

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