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HIV Infections

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Integrated epigenomic exposure signature discovery.

Epigenomics
The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Here we developed and implemented a machine learning algorithm, the exposure signature discove...

Using machine learning models to plan HIV services: Emerging opportunities in design, implementation and evaluation.

South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde
HIV/AIDS remains one of the world's most significant public health and economic challenges, with approximately 36 million people currently living with the disease. Considerable progress has been made to reduce the impact of HIV/AIDS in the past years...

Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data.

Scientific reports
Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV i...

"Where No One Has Gone Before": Questions to Ensure the Ethical, Rigorous, and Thoughtful Application of Artificial Intelligence in the Analysis of HIV Research.

The Journal of the Association of Nurses in AIDS Care : JANAC
ChatGPT, an artificial intelligence (AI) system released by OpenAI on November 30th, 2022, has upended scientific and educational paradigms, reshaping the way that we think about teaching, writing, and now research. Since that time, qualitative data ...

Novel Machine Learning HIV Intervention for Sexual and Gender Minority Young People Who Have Sex With Men (uTECH): Protocol for a Randomized Comparison Trial.

JMIR research protocols
BACKGROUND: Sexual and gender minority (SGM) young people are disproportionately affected by HIV in the United States, and substance use is a major driver of new infections. People who use web-based venues to meet sex partners are more likely to repo...

A comparative analysis of classical and machine learning methods for forecasting TB/HIV co-infection.

Scientific reports
TB/HIV coinfection poses a complex public health challenge. Accurate forecasting of future trends is essential for efficient resource allocation and intervention strategy development. This study compares classical statistical and machine learning mod...

Ameliorating Racial Disparities in HIV Prevention via a Nurse-Led, AI-Enhanced Program for Pre-Exposure Prophylaxis Utilization Among Black Cisgender Women: Protocol for a Mixed Methods Study.

JMIR research protocols
BACKGROUND: HIV pre-exposure prophylaxis (PrEP) is a critical biomedical strategy to prevent HIV transmission among cisgender women. Despite its proven effectiveness, Black cisgender women remain significantly underrepresented throughout the PrEP car...

Optimal STI controls for HIV patients based on an efficient deep Q learning method.

Journal of theoretical biology
We investigate an efficient computational tool to suggest useful treatment regimens for people infected with the human immunodeficiency virus (HIV). Structured treatment interruption (STI) is a regimen in which therapeutic drugs are periodically admi...

Using Machine Learning to Identify Patients at Risk of Acquiring HIV in an Urban Health System.

Journal of acquired immune deficiency syndromes (1999)
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...