Machine learning approaches identify immunologic signatures of total and intact HIV DNA during long-term antiretroviral therapy

Understanding the interplay between the HIV reservoir and the host immune system may yield insights into HIV persistence during antiretroviral therapy (ART) and inform strategies for a cure. Here, we applied machine learning (ML) approaches to cross-sectional high-parameter HIV reservoir and immunol...

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Bibliografiske detaljer

Principais autores:	Lesia Semenova, Yingfan Wang, Shane Falcinelli, Nancie Archin, Alicia D Cooper-Volkheimer, David M Margolis, Nilu Goonetilleke, David M Murdoch, Cynthia D Rudin, Edward P Browne
Format:	Artigo
Sprog:	Inglês
Udgivet:	eLife Sciences Publications Ltd 2024-09-01
Serier:	eLife
Fag:	HIV immune cells machine learning
Online adgang:	https://elifesciences.org/articles/94899
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