AIMC Topic: HIV Infections
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Evaluating machine learning algorithms for predicting HIV status among young Thai men who have sex with men.
BMJ health & care informatics
May 15, 2025
OBJECTIVE: This study aimed to develop machine learning (ML) models to predict HIV status and assessed the factors associated with HIV infection among young men who have sex with men (MSM) under the Universal Health Coverage (UHC) programme in Thaila...
"What Did You Say, ChatGPT?" The Use of AI in Black Women's HIV Self-Education: An Inductive Qualitative Data Analysis.
The Journal of the Association of Nurses in AIDS Care : JANAC
May 14, 2025
The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents unique opportunities and challenges in public health self-education. This study examined simulations with ChatGPT for its use in public education of sex...
Artificial Intelligence and Scientific Publishing.
The Journal of the Association of Nurses in AIDS Care : JANAC
May 13, 2025
Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan.
Journal of medical Internet research
May 12, 2025
BACKGROUND: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, management, and care. HIV stigma can negatively influence health behaviors. Surveys of the general public in Japan also demonstrated substantial gaps in knowle...
Integrating different approaches for the identification of new disruptors of HIV-1 capsid multimerization.
Biochemical and biophysical research communications
May 12, 2025
Human Immunodeficiency Virus (HIV) belongs to the Lentivirus genus, Retroviridae family, enveloped by a lipid bilayer within which the capsid protein encases the viral genome, reverse transcriptase, and integrase proteins, key components for viral re...
Machine learning to improve HIV screening using routine data in Kenya.
Journal of the International AIDS Society
Apr 1, 2025
INTRODUCTION: Optimal use of HIV testing resources accelerates progress towards ending HIV as a global threat. In Kenya, current testing practices yield a 2.8% positivity rate for new diagnoses reported through the national HIV electronic medical rec...
A Machine Learning Model for Diagnosing Opportunistic Infections in HIV Patients: Broad Applicability Across Infection Types.
Journal of cellular and molecular medicine
Mar 1, 2025
Opportunistic infections (OIs) are the leading cause of hospitalisation and mortality among Human Immunodeficiency Virus-infected (HIV-infected) patients. The diverse pathogen types and intricate clinical manifestations associated present a formidabl...
Using Machine Learning Techniques to Predict Viral Suppression Among People With HIV.
Journal of acquired immune deficiency syndromes (1999)
Mar 1, 2025
BACKGROUND: This study aims to develop and examine the performance of machine learning (ML) algorithms in predicting viral suppression among statewide people living with HIV (PWH) in South Carolina.
Convolutional neural network using magnetic resonance brain imaging to predict outcome from tuberculosis meningitis.
PloS one
Jan 1, 2025
INTRODUCTION: Tuberculous meningitis (TBM) leads to high mortality, especially amongst individuals with HIV. Predicting the incidence of disease-related complications is challenging, for which purpose the value of brain magnetic resonance imaging (MR...
Survival causal rule ensemble method considering the main effect for estimating heterogeneous treatment effects.
Statistics in medicine
Nov 30, 2024
With an increasing focus on precision medicine in medical research, numerous studies have been conducted in recent years to clarify the relationship between treatment effects and patient characteristics. The treatment effects for patients with differ...
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