doi.org/10.12688/f1000research.15591.1
Original paper

Revealing HIV viral load patterns using unsupervised machine learning and cluster summarization

..., Martin S. Zand
34
F1000Research
Volume: 7, Pages: 1144 - 1144
Published: Jul 27, 2018
Abstract
HIV RNA viral load (VL) is an important outcome variable in studies of HIV infected persons. There exists only a handful of methods which classify patients by VL patterns. Most methods place limits on the use of viral load measurements, are often specific to a particular study design, and do not account for complex, temporal variation. To address this issue, we propose a set of four unambiguous computable characteristics (features) of...
Paper Fields
Paper Details
Title
Revealing HIV viral load patterns using unsupervised machine learning and cluster summarization
DOI
doi.org/10.12688/f1000research.15591.1
Published Date
Jul 27, 2018
Journal
F1000Research
Volume
7
Pages
1144 - 1144
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