ReviewThe lancet. HIV2022
Application of artificial intelligence and machine learning for HIV prevention interventions.
Review in The lancet. HIV, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed, 51 citations in OpenAlex.
- Dating Applications as HIV Prevention Ecosystems in the Era of Digital Sexual Networks.Infectious disease reports · 2026Article
- Harnessing Artificial Intelligence in Health Research in Low-Income and Middle-Income Countries: Potential and Caution.Mayo Clinic proceedings. Digital health · 2026Review
- Evaluation of a Digital Intervention for Monitoring and Improving Medication Adherence Among Real-World e-Consumers of HIV Preexposure Prophylaxis in China: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2026Article
- Reimagining Paediatric HIV Care: Centering Infants and Young Children in Optimized, Integrated Models of Care.Journal of the International AIDS Society · 2026Article
- Harnessing machine learning models to repurpose drugs targeting HIV-1 integrase, protease, and reverse transcriptase.Scientific reports · 2026Article
- Federated Learning Performance Depends on Site Variation in Global HIV Data Consortia.medRxiv : the preprint server for health sciences · 2026Article
- Modeling of longitudinal immune profiles reveals distinct immunogenic signatures following five COVID-19 vaccinations among people living with HIV.Patterns (New York, N.Y.) · 2026Article
- Benchmark evaluation of large language models for clinical decision support in headache management.Journal of oral & facial pain and headache · 2026Article
- Innovative approaches for engaging adolescents in Primary HIV prevention: lessons from the peer-Led health education program in Nimule, South Sudan.Reproductive health · 2026Article
- Factors influencing late HIV presentation in China: results from logistic regression and Bayesian network analyses.BMC infectious diseases · 2026Article
- Predicting early infant diagnosis (EID) results for HIV exposed infants in a resource-limited setting using machine learning models: evidence from Amhara Public Health Institute data (2024/2025).BMC infectious diseases · 2026Article
- Artificial intelligence in HIV research: a structured review and task-oriented clinical framework.Frontiers in digital health · 2026Review
- Machine Learning Application in Enhancing HIV Management and Treatment Outcomes: Revolutionizing HIV Infection.Current HIV research · 2026Review
- Artificial intelligence in human immunodeficiency virus mutation prediction and drug design: Advancing personalized treatment and prevention.Pharmaceutical science advances · 2025Review
- Bridging Health Disparities in the Data-Driven World of Artificial Intelligence: A Narrative Review.Journal of racial and ethnic health disparities · 2025Review
- Formative evaluation of the acceptance of HIV prevention Artificial Intelligence chatbots by Black gay, bisexual, and other men who have sex with men in the Southern United States: Focus group study.PLOS digital health · 2025Article
- Machine Learning Identifies Sexual Behavior Subgroups Among Men Who Have Sex with Men in Switzerland.Archives of sexual behavior · 2025Article
- Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges.Nature communications · 2025Article
- The status of machine learning in HIV testing in South Africa: a qualitative inquiry with stakeholders in Gauteng province.Frontiers in digital health · 2025Article
- The application of machine learning in clinical microbiology and infectious diseases.Frontiers in cellular and infection microbiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
In 2019, the US Government announced its goal to end the HIV epidemic within 10 years, mirroring the initiatives set forth by UNAIDS. Public health prevention interventions are a crucial part of this ambitious goal. However, numerous challenges to this goal exist, including improving HIV awareness, increasing early HIV infection detection, ensuring rapid treatment, optimising resource distribution, and providing efficient prevention services for vulnerable populations. Artificial intelligence has had a pivotal role in revolutionising health care and has shown great potential in developing effective HIV prevention intervention strategies. Although artificial intelligence has been used in a few HIV prevention intervention areas, there are challenges to address and opportunities to explore.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.