Predicting sexually transmitted infections among men who have sex with men in Zimbabwe using deep learning and ensemble machine learning models.

There is a substantial increase in sexually transmitted infections (STIs) among men who have sex with men (MSM) globally. Unprotected sexual practices, multiple sex partners, criminalization, stigmatisation, fear of discrimination, substance use, poor access to care, and lack of early STI screening...

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Bibliografski detalji

Glavni autori:	Owen Mugurungi, Elliot Mbunge, Rutendo Birri-Makota, Innocent Chingombe, Munyaradzi Mapingure, Brian Moyo, Amon Mpofu, John Batani, Benhildah Muchemwa, Chesterfield Samba, Delight Murigo, Musa Sibindi, Enos Moyo, Tafadzwa Dzinamarira, Godfrey Musuka
Format:	Artigo
Jezik:	Inglês
Izdano:	Public Library of Science (PLoS) 2024-07-01
Serija:	PLOS Digital Health
Online pristup:	https://doi.org/10.1371/journal.pdig.0000541
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