AI Medical Compendium Journal:
Journal of acquired immune deficiency syndromes (1999)

Showing 1 to 8 of 8 articles

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.
Humans Machine Learning Middle Aged HIV Infections Viral Load Algorithms South Carolina Female Adult Male
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Using Machine Learning to Identify Patients at Risk of Acquiring HIV in an Urban Health System.

Journal of acquired immune deficiency syndromes (1999) Sep 1, 2024
BACKGROUND: Effective measures exist to prevent the spread of HIV. However, the identification of patients who are candidates for these measures can be a challenge. A machine learning model to predict risk for HIV may enhance patient selection for pr...
Humans HIV Infections Machine Learning Incidence Electronic Health Records Female Middle Aged Young Adult Risk Assessment Adult Adolescent Male
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Results From a Pilot Study of an Automated Directly Observed Therapy Intervention Using Artificial Intelligence With Conditional Economic Incentives Among Young Adults With HIV.

Journal of acquired immune deficiency syndromes (1999) Jun 1, 2024
BACKGROUND: Despite improvements in antiretroviral therapy (ART) availability, suboptimal adherence is common among youth with HIV (YWH) and can increase drug resistance and poor clinical outcomes. Our study examined an innovative mobile app-based in...
Humans Artificial Intelligence Pilot Projects Adolescent HIV Infections Viral Load Female Young Adult Adult Male Motivation California Florida Directly Observed Therapy Anti-HIV Agents Medication Adherence Mobile Applications
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Machine Learning Analysis Reveals Novel Neuroimaging and Clinical Signatures of Frailty in HIV.

Journal of acquired immune deficiency syndromes (1999) Aug 1, 2020
BACKGROUND: Frailty is an important clinical concern for the aging population of people living with HIV (PLWH). The objective of this study was to identify the combination of risk features that distinguish frail from nonfrail individuals.
Psychomotor Performance Neuroimaging Frailty CD4 Lymphocyte Count Anti-Retroviral Agents Algorithms Female Male Aging Middle Aged HIV Infections United States Humans Machine Learning
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Deep Learning Analysis of Cerebral Blood Flow to Identify Cognitive Impairment and Frailty in Persons Living With HIV.

Journal of acquired immune deficiency syndromes (1999) Dec 15, 2019
BACKGROUND: Deep learning algorithms of cerebral blood flow were used to classify cognitive impairment and frailty in people living with HIV (PLWH). Feature extraction techniques identified brain regions that were the strongest predictors.
Neuropsychological Tests Cerebrovascular Circulation Magnetic Resonance Imaging Frailty Neuroimaging Female Adult Male Middle Aged Deep Learning Cognitive Dysfunction HIV Infections Anti-HIV Agents Humans Brain
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Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.

Journal of acquired immune deficiency syndromes (1999) Feb 1, 2018
OBJECTIVE: Universal HIV screening programs are costly, labor intensive, and often fail to identify high-risk individuals. Automated risk assessment methods that leverage longitudinal electronic health records (EHRs) could catalyze targeted screening...
Middle Aged Risk Assessment Infant Adolescent HIV Infections Cohort Studies Child, Preschool Aged, 80 and over Young Adult Adult Algorithms Male Decision Support Techniques Infant, Newborn Electronic Health Records Humans Risk Factors Female Aged Child Mass Screening Natural Language Processing Automation New York City
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Toward Automating HIV Identification: Machine Learning for Rapid Identification of HIV-Related Social Media Data.

Journal of acquired immune deficiency syndromes (1999) Feb 1, 2017
INTRODUCTION: "Social big data" from technologies such as social media, wearable devices, and online searches continue to grow and can be used as tools for HIV research. Although researchers can uncover patterns and insights associated with HIV trend...
Machine Learning HIV Infections Time Factors Social Media Humans Statistics as Topic Epidemiologic Methods Risk-Taking
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Super Learner Analysis of Electronic Adherence Data Improves Viral Prediction and May Provide Strategies for Selective HIV RNA Monitoring.

Journal of acquired immune deficiency syndromes (1999) May 1, 2015
OBJECTIVE: Regular HIV RNA testing for all HIV-positive patients on antiretroviral therapy (ART) is expensive and has low yield since most tests are undetectable. Selective testing of those at higher risk of failure may improve efficiency. We investi...
Treatment Failure Prospective Studies Middle Aged Humans Female Cohort Studies Assessment of Medication Adherence HIV Infections Artificial Intelligence Adult Anti-HIV Agents Longitudinal Studies Decision Support Techniques Male Drug Monitoring RNA, Viral
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