AIMC Topic: HIV Infections
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Classification of radiology reports for falls in an HIV study cohort.
Journal of the American Medical Informatics Association : JAMIA
Nov 13, 2015
OBJECTIVE: To identify patients in a human immunodeficiency virus (HIV) study cohort who have fallen by applying supervised machine learning methods to radiology reports of the cohort.
Measurement of viral load by the automated Abbott real-time HIV-1 assay using dried blood spots collected and processed in Malawi and Mozambique.
South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde
Nov 8, 2015
BACKGROUND: The use of dried blood spots (DBS) for HIV-1 viral load quantification can greatly improve access to viral monitoring for HIV-infected patients receiving treatment in resource-limited settings.
High frequency of neurosyphilis in HIV-positive patients diagnosed with early syphilis.
HIV medicine
Sep 10, 2015
BACKGROUND: Syphilis is an infection frequently seen with HIV, and European guidelines on the management of syphilis suggest that HIV-infected patients may have an increased risk of early neurological involvement, sometimes asymptomatic. Recent study...
Comparative risk of failure of ABC/3TC or TDF/FTC based first-line regimens in patients with a high viral load.
HIV medicine
Aug 26, 2015
OBJECTIVES: To compare the efficacy, in current clinical practice, of first regimens containing abacavir with lamivudine (ABC/3TC) or tenofovir with emtricitabine (TDF/FTC) in patients with baseline viral load ≥100,000 HIV-1 RNA copies/mL.
Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.
PLoS computational biology
Apr 13, 2015
The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector ce...
Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.
Statistics in medicine
Oct 15, 2014
Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predicti...
Machine learning for personalized risk assessment of HIV, syphilis, gonorrhoea and chlamydia: A systematic review and meta-analysis.
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
Aug 1, 2025
BACKGROUND: Machine learning (ML) shows promise for sexually transmitted infection (STI) risk prediction, but systematic evidence of its effectiveness remains fragmented.
Significant associations between high-risk sexual behaviors and enterotypes of gut microbiome in HIV-negative men who have sex with men.
mSphere
Jul 29, 2025
UNLABELLED: Gut microbiome of men who have sex with men (MSM) exhibits distinctive characteristics compared with general populations. The dysbiosis of the gut microbiome in MSM is also associated with the onset and evolution of HIV infection. Enterot...
Scalable and robust machine learning framework for HIV classification using clinical and laboratory data.
Scientific reports
May 28, 2025
Human Immunodeficiency Virus (HIV) is a retrovirus that weakens the immune system, increasing vulnerability to infections and cancers. HIV spreads primarily via sharing needles, from mother to child during childbirth or breastfeeding, or unprotected ...
Development of a machine learning prediction model for loss to follow-up in HIV care using routine electronic medical records in a low-resource setting.
BMC medical informatics and decision making
May 19, 2025
BACKGROUND: Despite the global commitment to ending AIDS by 2030, the loss of follow-up (LTFU) in HIV care remains a significant challenge. To address this issue, a data-driven clinical decision tool is crucial for identifying patients at greater ris...
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