Transforming clinical virology with AI, machine learning and deep learning: a comprehensive review and outlook

A Padhi, A Agarwal, SK Saxena, CDS Katoch - VirusDisease, 2023 - Springer
In the rapidly evolving field of clinical virology, technological advancements have always
played a pivotal role in driving transformative changes. This comprehensive review delves …

Social and behavioral impacts of COVID-19 on people living with HIV: review of the first year of research

SC Kalichman, R El-Krab - Current HIV/AIDS Reports, 2022 - Springer
Abstract Purpose of the Review The SARS-CoV-2 (COVID-19) pandemic brought
unprecedented social change with the most severe impacts on the most vulnerable …

Progress of the gulf cooperation council (gcc) countries towards achieving the 95-95-95 UNAIDS targets: a review

SA Awaidy, RM Ghazy, O Mahomed - Journal of epidemiology and global …, 2023 - Springer
Abstract Background In 2014, the Joint United Nations Programme on HIV/AIDS (UNAIDS)
and partners launched the 90-90-90 targets. These were further updated to correspond to 95 …

Application of artificial intelligence and machine learning for HIV prevention interventions

Y **ang, J Du, K Fujimoto, F Li, J Schneider, C Tao - The Lancet HIV, 2022 - thelancet.com
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 …

Early stage HIV diagnosis using optimized ensemble learning technique

R Saha, L Malviya, A Jadhav, R Dangi - Biomedical Signal Processing and …, 2024 - Elsevier
Human immunodeficiency Virus most commonly known as HIV, is a retrovirus that attacks
and weakens the immune system, leaving the body vulnerable to opportunistic infections …

“There hasn't been a push to identify patients in the emergency department”—Staff perspectives on automated identification of candidates for pre-exposure …

SA Devlin, AK Johnson, KA Stanford, S Haider… - PLoS …, 2024 - journals.plos.org
Automated algorithms for identifying potential pre-exposure prophylaxis (PrEP) candidates
are effective among men, yet often fail to detect cisgender women (hereafter referred to as …

[HTML][HTML] Early diagnosis of HIV cases by means of text mining and machine learning models on clinical notes

R Morales-Sánchez, S Montalvo, A Riaño… - Computers in Biology …, 2024 - Elsevier
Undiagnosed and untreated human immunodeficiency virus (HIV) infection increases
morbidity in the HIV-positive person and allows onward transmission of the virus. Minimizing …

Pediatric provider utilization of a clinical decision support alert and association with HIV pre-exposure prophylaxis prescription rates

CT Chan, M Vo, J Carlson, T Lee… - Applied Clinical …, 2022 - thieme-connect.com
Objectives An electronic clinical decision support (CDS) alert can provide real-time provider
support to offer pre-exposure prophylaxis (PrEP) to youth at risk for human …

Predicting low density lipoprotein cholesterol target attainment using machine learning in patients with coronary artery disease receiving moderate-dose statin therapy

J Han, Y Kim, HJ Kang, J Seo, H Choi, M Kim, G Kee… - Scientific Reports, 2025 - nature.com
Low-density lipoprotein cholesterol (LDL-C) is an important factor in the development of
cardiovascular disease, making its management a key aspect of cardiovascular health …

Multicenter development and validation of a model for predicting retention in care among people with HIV

JP Ridgway, A Ajith, EE Friedman, MJ Mugavero… - AIDS and Behavior, 2022 - Springer
Predictive analytics can be used to identify people with HIV currently retained in care who
are at risk for future disengagement from care, allowing for prioritization of retention …