A comparative study of logistic regression based machine learning techniques for prediction of early virological suppression in antiretroviral initiating HIV patients

A comparative study of logistic regression based machine learning techniques for prediction of early virological suppression in antiretroviral initiating HIV patients

Abstract Background Treatment with effective antiretroviral therapy (ART) lowers morbidity and mortality among HIV positive individuals. Effective highly active antiretroviral therapy (HAART) should lead to undetectable viral load within 6 months of initiation of therapy. Failure to achieve and main...

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Bibliographic Details
Main Authors: Kuteesa R. Bisaso, Susan A. Karungi, Agnes Kiragga, Jackson K. Mukonzo, Barbara Castelnuovo
Format: Article
Language:English
Published: BMC 2018-09-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Prediction
Viral suppression
Machine learning
Multitask temporal logistic regression
Patient specific survival prediction
Logistic regression
Online Access:http://link.springer.com/article/10.1186/s12911-018-0659-x

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http://link.springer.com/article/10.1186/s12911-018-0659-x

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