Unsupervised machine learning predicts future sexual behaviour and sexually transmitted infections among HIV-positive men who have sex with men | Zendy

Sara Andresen | Zendy; Suraj Balakrishna | Zendy; Catrina Mugglin | Zendy; Axel J. Schmidt | Zendy; Dominique L. Braun | Zendy; Alex Marzel | Zendy; Thanh Lecompte | Zendy; Katharine Darling | Zendy; Benno Röthlisberger | Zendy; Patrick Schmid | Zendy; Enos Bernasconi | Zendy; Huldrych F. Günthard | Zendy; Andri Rauch | Zendy; Roger D. Kouyos | Zendy; Luisa SalazarVizcaya | Zendy

Open Access

Unsupervised machine learning predicts future sexual behaviour and sexually transmitted infections among HIV-positive men who have sex with men

Author(s) -

Sara Andresen,

Suraj Balakrishna,

Catrina Mugglin,

Axel J. Schmidt,

Dominique L. Braun,

Alex Marzel,

Thanh Lecompte,

Katharine Darling,

Benno Röthlisberger,

Patrick Schmid,

Enos Bernasconi,

Huldrych F. Günthard,

Andri Rauch,

Roger D. Kouyos,

Luisa SalazarVizcaya

Publication year - 2022

Publication title -

plos computational biology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.628

H-Index - 182

eISSN - 1553-7358

pISSN - 1553-734X

DOI - 10.1371/journal.pcbi.1010559

Subject(s) - akaike information criterion , cluster analysis , bayesian information criterion , machine learning , men who have sex with men , likelihood ratio test , receiver operating characteristic , artificial intelligence , epidemiology , bayesian probability , human immunodeficiency virus (hiv) , computer science , statistics , medicine , mathematics , family medicine , syphilis

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