Predicting HIV infection in the decade (2005–2015) pre-COVID-19 in Zimbabwe: a supervised classification-based machine learning approach
RB Birri Makota, E Musenge - PLOS Digital Health, 2023 - journals.plos.org
The burden of HIV and related diseases have been areas of great concern pre and post the
emergence of COVID-19 in Zimbabwe. Machine learning models have been used to predict …
emergence of COVID-19 in Zimbabwe. Machine learning models have been used to predict …
Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in …
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 …
as HIV-related morbidity and mortality in HIV-positive patients. Despite the expanded …
Machine learning prediction of adolescent HIV testing services in Ethiopia
MS Alie, Y Negesse - Frontiers in Public Health, 2024 - frontiersin.org
Background Despite endeavors to achieve the Joint United Nations Programme on
HIV/AIDS 95-95-95 fast track targets established in 2014 for HIV prevention, progress has …
HIV/AIDS 95-95-95 fast track targets established in 2014 for HIV prevention, progress has …
The role of machine learning in HIV risk prediction
Despite advances in reducing HIV-related mortality, persistently high HIV incidence rates
are undermining global efforts to end the epidemic by 2030. The UNAIDS Fast-track targets …
are undermining global efforts to end the epidemic by 2030. The UNAIDS Fast-track targets …
Validation and improvement of a machine learning model to predict interruptions in antiretroviral treatment in South Africa
R Esra, J Carstens, S Le Roux, T Mabuto… - JAIDS Journal of …, 2023 - journals.lww.com
Study design: RE, JC, KSS, LDV, SL, TM, MM; Data Collection: ME; Data Analysis: RE, JC,
KSS; Data Interpretation: RE, JC, KSS, MM; Supervision: MM; Writing–original draft: RE; …
KSS; Data Interpretation: RE, JC, KSS, MM; Supervision: MM; Writing–original draft: RE; …
Development of a Machine Learning Modeling Tool for Predicting Human Immunodeficiency Virus Incidence Using Public Health Data From a County in the Southern …
CS Saldana, E Burkhardt, A Pennisi… - Clinical Infectious …, 2024 - academic.oup.com
Background Advancements in machine learning (ML) have improved the accuracy of
models that predict human immunodeficiency virus (HIV) incidence. These models have …
models that predict human immunodeficiency virus (HIV) incidence. These models have …
Development and Evaluation of a Digital HIV Risk Assessment Tool Incorporated Within an App-Based Self-Testing Program
Background: Low-risk perception is an important barrier to the utilization of HIV services. In
this context, offering an online platform for people to assess their risk of HIV and inform their …
this context, offering an online platform for people to assess their risk of HIV and inform their …
Using machine learning models to plan HIV services: Emerging opportunities in design, implementation and evaluation
T Dzinamarira, E Mbunge, I Chingombe… - South African …, 2024 - samajournals.co.za
HIV/AIDS remains one of the world's most significant public health and economic
challenges, with approximately 36 million people currently living with the disease …
challenges, with approximately 36 million people currently living with the disease …
[PDF][PDF] Machine learning prediction of
MS Alie, Y Negesse - 2024 - researchgate.net
Background: Despite endeavors to achieve the Joint United Nations Programme on
HIV/AIDS 95-95-95 fast track targets established in 2014 for HIV prevention, progress has …
HIV/AIDS 95-95-95 fast track targets established in 2014 for HIV prevention, progress has …
[PDF][PDF] MAJOR ARTICLE
HY Chu - 2024 - bedford.io
Background. SARS-CoV-2 antigen-detection rapid diagnostic tests (Ag-RDTs) have become
widely utilized but longitudinal characterization of their community-based performance …
widely utilized but longitudinal characterization of their community-based performance …