Super Learner Analysis of Electronic Adherence Data Improves Viral Prediction and May Provide Strategies for Selective HIV RNA Monitoring
Author(s) -
Maya Petersen,
Erin LeDell,
Joshua Schwab,
Varada Sarovar,
Robert A. Gross,
Nancy Reynolds,
Jessica E. Haberer,
Kathy Goggin,
Carol E. Golin,
Julia H. Arnsten,
Marc I. Rosen,
Robert H. Remien,
David Etoori,
Ira B. Wilson,
Jane M. Simoni,
Judith A. Erlen,
Mark J. van der Laan,
Honghu Liu,
David R. Bangsberg
Publication year - 2015
Publication title -
carolina digital repository (university of north carolina at chapel hill)
Language(s) - English
DOI - 10.17615/4n0c-e627
Subject(s) - human immunodeficiency virus (hiv) , viral load , computer science , virology , medicine , computational biology , biology
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