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Paper Details

Random forest machine learning algorithm predicts virologic outcomes among HIV infected adults in Lausanne, Switzerland using electronically monitored combined antiretroviral treatment adherence.
AIDS Care
8
2021
CD4, HIV, HIV infected, Patients, RNA, RNA VL, RNA class, patients, people
Adult, Algorithms, Anti-HIV Agents, Antiretroviral Therapy, Highly Active, CD4 Lymphocyte Count, Cohort Studies, Female, HIV Infections, Humans, Machine Learning, Male, Medication Adherence, Retrospective Studies, Switzerland, Treatment Outcome, Viral Load
Author NameAffiliation
Susan KamalCommunity pharmacy, School of pharmaceutical sciences, University of Geneva, University of Lausanne
Susan KamalUniversity of California Institute for Prediction Technology, University of California los angeles
Susan KamalDavid Geffen School of Medicine, University of California los angeles
Susan KamalCommunity pharmacy, University of Lausanne
Susan KamalCommunity pharmacy, School of pharmaceutical sciences, University of Geneva, University of Lausanne
Susan KamalCommunity pharmacy, University of Lausanne
Susan KamalDavid Geffen School of Medicine, University of California los angeles
Susan KamalUniversity of California Institute for Prediction Technology, University of California los angeles
John UrataDavid Geffen School of Medicine, University of California los angeles
John UrataUniversity of California Institute for Prediction Technology, University of California los angeles
John UrataDavid Geffen School of Medicine, University of California los angeles
John UrataUniversity of California Institute for Prediction Technology, University of California los angeles
Matthias CavassiniLausanne university hospital, University of Lausanne
Matthias CavassiniLausanne university hospital, University of Lausanne
Honghu LiuUniversity of California los angeles
Honghu LiuDivision of General Internal Medicine and Health Services Research, University of California los angeles
Honghu LiuFielding School of Public Health, University of California los angeles
Honghu LiuUniversity of California los angeles
Honghu LiuFielding School of Public Health, University of California los angeles
Honghu LiuDivision of General Internal Medicine and Health Services Research, University of California los angeles
Roger D KouyosDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich
Roger D KouyosDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich
Olivier BugnonCommunity pharmacy, School of pharmaceutical sciences, University of Geneva, University of Lausanne
Olivier BugnonCommunity pharmacy, University of Lausanne
Olivier BugnonCommunity pharmacy, School of pharmaceutical sciences, University of Geneva, University of Lausanne
Olivier BugnonCommunity pharmacy, University of Lausanne
Wei WangUniversity of California Institute for Prediction Technology, University of California los angeles
Wei WangUniversity of California los angeles
Wei WangUniversity of California Institute for Prediction Technology, University of California los angeles
Wei WangUniversity of California los angeles
Marie Paule SchneiderCommunity pharmacy, School of pharmaceutical sciences, University of Geneva, University of Lausanne
Marie Paule SchneiderCommunity pharmacy, University of Lausanne
Marie Paule SchneiderCommunity pharmacy, School of pharmaceutical sciences, University of Geneva, University of Lausanne
Marie Paule SchneiderCommunity pharmacy, University of Lausanne
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