Open AccessUnsupervised 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 E A Darling,
Jan A Roth,
Patrick Schmid,
Enos Bernasconi,
Huldrych F Günthard,
Andri Rauch,
Roger D. Kouyos,
Luisa SalazarVizcaya
Publication year - 2022
Publication title -
plos computational biology/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 , men who have sex with men , bayesian information criterion , machine learning , likelihood ratio test , receiver operating characteristic , epidemiology , artificial intelligence , human immunodeficiency virus (hiv) , computer science , statistics , medicine , mathematics , family medicine , syphilis