ReviewFrontiers in microbiology2025
AI applications in HIV research: advances and future directions.
Review in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Feasibility of AI-Enabled Chatbots for Pre-consultation in HIV Care in Northern Nigeria.International journal of behavioral medicine · 2026Article
- A Comparative Evaluation Framework Integrating Machine Learning and Deep Learning Models with ADME-Based Pharmacokinetic Assessment for HIV-Related Compounds.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Is the molecular microenvironment of the latent HIV reservoir predictable using deep learning approaches?Journal of virology · 2026Review
- Review
- Performance comparison of large language models for medication counseling in people living with HIV.Frontiers in public health · 2026Article
- HIV-associated immune remodeling in cervical cancer: implications for immunotherapy, biomarkers, and trial design.Frontiers in immunology · 2026Review
- HIV case management using agent-based modeling approach subject to antiretroviral therapy and lifestyle treatment plan.Scientific reports · 2025Article
- AI Methods Tailored to Influenza, RSV, HIV, and SARS-CoV-2: A Focused Review.Pathogens (Basel, Switzerland) · 2025Review
- HIV-1 and Artificial Intelligence: From Molecular Insight to Population Impact.Journal of AIDS and HIV treatment · 2025Article
- Artificial intelligence and machine learning in the development of vaccines and immunotherapeutics-yesterday, today, and tomorrow.Frontiers in artificial intelligence · 2025Review
- The status of machine learning in HIV testing in South Africa: a qualitative inquiry with stakeholders in Gauteng province.Frontiers in digital health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the increasing application of artificial intelligence (AI) in medical research, studies on the human immunodeficiency virus type 1(HIV-1) and acquired immunodeficiency syndrome (AIDS) have become more in-depth. Integrating AI with technologies like single-cell sequencing enables precise biomarker identification and improved therapeutic targeting. This review aims to explore the advancements in AI technologies and their applications across various facets of HIV research, including viral mechanisms, diagnostic innovations, therapeutic strategies, and prevention efforts. Despite challenges like data limitations and model interpretability, AI holds significant potential in advancing HIV-1 management and contributing to global health goals.
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.