HIV/AIDS

Risk Prediction Modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: Leveraging Machine Learning

Pre-procedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and benchmarking hospital performance. This study aimed to identify pre-procedural factors to predict the risk of 30-day all-cause mortality post-PCI using machine learning (ML) approaches. The study analysed 93,055 consecutive PCI procedures. Boruta feature ...

Association between zidovudine and adverse pregnancy outcomes/congenital malformations: A pharmacovigilance study using FAERS data

Zidovudine (AZT), a key antiretroviral drug used for HIV treatment and preventing mother-to-child transmission, has insufficient post-marketing pharmacovigilance regarding pregnancy outcomes and congenital disorders. This pharmacovigilance study analyzed adverse event (AE) reports associated with zidovudine from the U.S. FDA Adverse Event Reporting System (FAERS) database (Q1 2004–Q4 2024) to asse...

Application of Extreme Gradient Boosting to predict NCD-HIV/AIDS comorbidity in young adults in Malawi

The fight to achieve Sustainable Development Goal 3.3 and 3.4 by 2030 requires data driven approaches and appropriate methodologies that would enable ...

Limited Predictability of Client Attendance in a Support Program for HIV Vertical Transmission Prevention: A Comparison of Machine Learning and Community Health Worker Predictions

Client attendance is vital for the success of HIV vertical transmission prevention programs, yet 23.4% of clients missed follow-up appointments after ...

Atherosclerosis biomarkers via mitochondrial permeability transition necrosis gene analysis

Atherosclerosis (AS) is a major cause for cardiovascular disease, and mitochondrial permeability transition driven necrosis (MPTDN) is often associate...

CardiacGPT™: A Real-Time AI Assistant for Intraoperative Guidance and Postoperative Decision Support in Cardiac Surgery

Cardiac surgery is one of the most complex and high-stakes areas of medicine, where intraoperative decisions must be made within seconds and incomplet...

Candidate Correlates of Protection in the HVTN505 HIV-1 Vaccine Efficacy Trial Identified by Positive-Unlabeled Learning

With a goal of unveiling mechanisms by which vaccines can provide protection against HIV-1 acquisition, several studies have explored correlates of ri...

Predictive Modelling’s role in Improving Pre-exposure Prophylaxis (PrEP) Uptake in High-Risk HIV Groups in Africa: An Integrative Scoping Review

This scoping review explores how predictive modelling can strengthen pre-exposure prophylaxis (PrEP) uptake among high-risk populations in Africa, whe...

ViraLite: An Ultracompact HIV Viral Load Self-Testing System with Internal Quality Control

The availability of effective antiretroviral therapy has made HIV manageable, provided patients have consistent access to routine viral load (VL) test...

Foundation model embeddings enable cardiovascular screening for people living with HIV in Vietnam using wearable signals

Cardiovascular disease (CVD) screening faces significant challenges in resource-limited settings, where infrastructure and computational constraints p...

Forecasting trends of HIV infection using deep learning models in East Gojjam zone, North West Ethiopia, 2025

The growing burden of HIV/AIDS, particularly in sub-Saharan Africa, presents a significant public health challenge, characterized by increasing morbid...

The Cognitive Safety Net: Comparing Human and AI Diagnostic Reasoning during Complex Clinical Situations

Diagnostic error in high-stakes clinical environments remains a significant cause of preventable harm. While a new generation of customisable digital ...

Beyond Accuracy: An Efficiency- and Safety-Aware Framework for Evaluating Clinical AI with Large Language Models

Large language models (LLMs) demonstrate strong performance on medical reasoning tasks, but current evaluation approaches focus primarily on accuracy,...

Machine Learning Approaches to Identify Communities with High HIV Prevalence in Resource-Limited Settings using Social, Economic and Behavioral Data

Identifying communities with high HIV prevalence is crucial for public health officials, researchers, and policymakers to effectively monitor the epid...

How effective is generative AI advice for the academic advancement of faculty?

The SingHealth Duke-NUS Academic Medical Center manages over 2,800 clinical faculty members and processes over 400 appointments and promotions annuall...

Developing Predictive Algorithms for Patient Retention Using Machine Learning and Deep Learning to Improve HIV Care in Uganda

Achieving high retention of people living with HIV (PLHIV) in care remains a challenge in Uganda, despite substantial progress towards UNAIDS 95-95-95...

Synthetic Data for Equitable Artificial Intelligence in Rapid Diagnostic Test Interpretation

Rapid diagnostic tests (RDTs) support affordable disease diagnosis. Machine learning (ML) can improve RDT interpretation but often relies on large, pr...

Evaluating the acceptability, usability and clinical appropriateness of Your Path, an AI-powered tool facilitating relevant access to HIV services post-HIV self-testing in South Africa

Timely linkage to HIV prevention and treatment services following HIV self-testing (HIVST) remains a challenge in many countries. While HIVST offers p...

Generalizable AI predicts immunotherapy outcomes across cancers and treatments

Immune checkpoint inhibitors have become standard care across many cancers, but most patients do not respond. Predicting response remains challenging ...

Evaluating Large Language Models for Colonoscopy Preparation Assistance: Correctness and Diversity in Synthetic Dialogues

Colorectal cancer is the third leading cause of cancer-related deaths in the United States, and colonoscopy remains the gold standard for early detect...