AIMC Topic: HIV Infections
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[Incidence and determinants of viral load rebound in people receiving multi-month dispensing of antiretroviral therapy at the Regional Annex Hospital of Dschang from 2018-2023].
The Pan African medical journal
Nov 12, 2024
INTRODUCTION: in Cameroon, multi-month dispensing (MMD) of antiretrovirals (ARVs) was introduced to improve treatment adherence among people living with HIV (PLHIV). However, this strategy has limitations that may lead to viral load rebound. The purp...
Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.
Scientific reports
Nov 4, 2024
This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infection, identifying candidate hub genes and potential drugs using bioinformatics and machine learning. Datasets for HIV (GSE 37250) and monkeypox (GSE 2412...
Predicting Treatment Outcomes in Patients with Drug-Resistant Tuberculosis and Human Immunodeficiency Virus Coinfection, Using Supervised Machine Learning Algorithm.
Pathogens (Basel, Switzerland)
Oct 24, 2024
Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strategy in 2035. A descriptive, retrospective review of medical records of patients, who were diagnosed wi...
Explainable artificial intelligence and domain adaptation for predicting HIV infection with graph neural networks.
Annals of medicine
Oct 17, 2024
OBJECTIVE: Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and performing domain adaptation to evaluate model transferability across different datasets.
The first AI-based Chatbot to promote HIV self-management: A mixed methods usability study.
HIV medicine
Oct 10, 2024
BACKGROUND: We developed MARVIN, an artificial intelligence (AI)-based chatbot that provides 24/7 expert-validated information on self-management-related topics for people with HIV. This study assessed (1) the feasibility of using MARVIN, (2) its usa...
HIV-1 M group subtype classification using deep learning approach.
Computers in biology and medicine
Oct 5, 2024
Traditionally, the classification of HIV-1 M group subtypes has depended on statistical methods constrained by sample sizes. Here HIV-1-M-SPBEnv was proposed as the first deep learning-based method for classifying HIV-1 M group subtypes via env gene ...
Prevention of adverse HIV treatment outcomes: machine learning to enable proactive support of people at risk of HIV care disengagement in Tanzania.
BMJ open
Sep 24, 2024
OBJECTIVES: This study aimed to develop a machine learning (ML) model to predict disengagement from HIV care, high viral load or death among people living with HIV (PLHIV) with the goal of enabling proactive support interventions in Tanzania. The alg...
Machine learning approaches identify immunologic signatures of total and intact HIV DNA during long-term antiretroviral therapy.
eLife
Sep 9, 2024
Understanding the interplay between the HIV reservoir and the host immune system may yield insights into HIV persistence during antiretroviral therapy (ART) and inform strategies for a cure. Here, we applied machine learning (ML) approaches to cross-...
Integrated epigenomic exposure signature discovery.
Epigenomics
Sep 3, 2024
The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Here we developed and implemented a machine learning algorithm, the exposure signature discove...
Novel Machine Learning HIV Intervention for Sexual and Gender Minority Young People Who Have Sex With Men (uTECH): Protocol for a Randomized Comparison Trial.
JMIR research protocols
Aug 20, 2024
BACKGROUND: Sexual and gender minority (SGM) young people are disproportionately affected by HIV in the United States, and substance use is a major driver of new infections. People who use web-based venues to meet sex partners are more likely to repo...
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