[HTML][HTML] Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized …

DN Mamo, TM Yilma, M Fekadie, Y Sebastian… - BMC Medical Informatics …, 2023 - Springer
Background Treatment with effective antiretroviral therapy (ART) reduces viral load as well
as HIV-related morbidity and mortality in HIV-positive patients. Despite the expanded …

Artificial intelligence and machine learning based prediction of viral load and CD4 status of people living with HIV (PLWH) on anti-retroviral treatment in Gedeo Zone …

BT Seboka, DE Yehualashet… - International Journal of …, 2023 - Taylor & Francis
Background Despite the success made in scaling up HIV treatment activities, there remains
a tremendous unmet demand for the monitoring of the disease progression and treatment …

[HTML][HTML] A comparative study of logistic regression based machine learning techniques for prediction of early virological suppression in antiretroviral initiating HIV …

KR Bisaso, SA Karungi, A Kiragga, JK Mukonzo… - BMC medical informatics …, 2018 - Springer
Background Treatment with effective antiretroviral therapy (ART) lowers morbidity and
mortality among HIV positive individuals. Effective highly active antiretroviral therapy …

Achieving the third 95 in sub-Saharan Africa: application of machine learning approaches to predict viral failure

AL Esber, NF Dear, D King, LV Francisco, V Sing'oei… - AIDS, 2023 - journals.lww.com
Objective: Viral failure in people with HIV (PWH) may be influenced by multiple
sociobehavioral, clinical, and context-specific factors, and supervised learning approaches …

Machine learning to predict retention and viral suppression in South African HIV treatment cohorts

M Maskew, K Sharpey-Schafer, LD Voux, J Bor… - medRxiv, 2021 - medrxiv.org
Abstract Background To optimize South Africa's HIV response and reach PEPFAR's 95: 95:
95 targets require same day initiations and patients successfully remaining on antiretroviral …

[HTML][HTML] Incidence, survival time and associated factors of virological failure among adult HIV/AIDS patients on first line antiretroviral therapy in St. Paul's Hospital …

DE Andarge, HE Hailu, T Menna - Plos one, 2022 - journals.plos.org
Introduction Human Immune deficiency Virus or Acquired Immune deficiency Syndrome
(HIV/AIDS) is a pandemic affecting millions around the world. The 2020 the Joint United …

Increased virological failure and determinants among HIV patients on highly active retroviral therapy in Adigrat General Hospital, Northern Ethiopia, 2019: hospital …

H Negash, M Welay, H Legese… - Infection and drug …, 2020 - Taylor & Francis
Background In Ethiopia, despite the integrated implementation of antiretroviral therapy since
2005, the human immunodeficiency virus remains a public health concern. Managing and …

Predictive analytics using machine learning to identify ART clients at health system level at greatest risk of treatment interruption in Mozambique and Nigeria

J Stockman, J Friedman, J Sundberg… - JAIDS Journal of …, 2022 - journals.lww.com
Background: A core objective of HIV/AIDS programming is keeping clients on treatment to
improve their health outcomes and to limit spread. Machine learning and artificial …

[HTML][HTML] Determinants of virological failure among patients on first line highly active antiretroviral therapy (HAART) in Southwest Ethiopia: A case-control study

B Bogale, A Asefa, A Destaw, G Midaksa… - Frontiers in Public …, 2022 - frontiersin.org
Background Virological failure remains a public health concern among patients with human
immunodeficiency virus (HIV) after treatment initiation. Ethiopia is one of the countries that …

Designing a predictive model for antiretroviral regimen at the antiretroviral therapy center in Chiro Hospital, Ethiopia

G Nemomsa, M Azath - Journal of Healthcare Engineering, 2021 - Wiley Online Library
Nowadays, the huge amount of patient's data significantly increases with respect to the time
in repositories and data mining is increasingly used as an emerging research area in …