Universal precautions

Electronic Health Record-Based Prediction Models to Inform Decisions about HIV Pre-exposure Prophylaxis: A Systematic Review

Several clinical prediction models have been developed using electronic health records data to help inform decisions about HIV pre-exposure prophylaxis (PrEP) prescribing, but the characteristics and quality of these models have not been systematically assessed. We identified and critically appraised the characteristics and quality of studies reporting the development of electronic health records ...

Machine learning models for tuberculous pleural effusion diagnosis in Africa setting

Traditional diagnostic methods for Tuberculous pleural effusion (TPE) are often limited by their invasiveness, low sensitivity, and lack of accessibility. This study aims to develop and evaluate ML models for diagnosing TPE in African contexts, using readily available clinical and laboratory data. A cross-sectional study carried out in Yaoundé, Cameroon (2018-2023), included patients with non-puru...

A Multi-pathogen Hospitalization Forecasting Model for the United States: An Optimized Geo-Hierarchical Ensemble Framework

Accurate forecasting of infectious diseases is crucial for timely public health response. Ensemble frameworks have shown promising outcomes in short-t...

Predicting Hypertension Among HIV Patients on Antiretroviral Therapy in Rural Eastern Cape, South Africa Using Machine Learning

Hypertension continues to be a major challenge in developing countries like South Africa, as it significantly contributes to the cardiovascular diseas...

Surveying the Literature on Implementation Determinants and Strategies for HIV Structural Interventions: A Systematic Review Protocol

Despite improvements in HIV prevention, treatment, and surveillance, vast disparities remain in access, uptake, and adherence of evidence-based interv...

Generalizable Prediction of Alzheimer Disease Pathologies with a Scalable Annotation Tool and an High-Accuracy Model

Characterizing the cardinal neuropathologies in Alzheimer disease (AD) can be laborious, time consuming, and susceptible to intra- and inter-observer ...

Alterations in the hepatic microenvironment following direct-acting antiviral therapy for chronic hepatitis C

Background and aims. The first direct-acting antivirals (DAAs) to treat the viral hepatitis C (HCV) became available in 2011. Despite numerous clinica...

Designing AI-powered healthcare assistants to effectively reach vulnerable populations with health care services: A discrete choice experiment among South African university students

South African young adults are at increased risk for HIV acquisition and other non-communicable diseases and face significant barriers to accessing he...

Plasma proteomics for novel biomarker discovery in childhood tuberculosis

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Curren...

Predicting Suicidality in people living with HIV in Uganda: A Machine Learning Approach

People living with HIV (PLWH) are more likely to experience suicidal thoughts and exhibit suicidal behavior than the general population. However, ther...

irAE-GPT: Leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets

Large language models (LLMs) have emerged as transformative technologies, revolutionizing natural language understanding and generation across various...

Tuberculosis disease severity assessment using clinical variables and radiology enabled by artificial intelligence

Radiology can define tuberculosis (TB) severity and may guide duration of treatment, however the optimal radiological metric to use and which clinical...

The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis

In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza. However, it ...

Prediction of the infecting organism in peritoneal dialysis patients with acute peritonitis using interpretable Tsetlin Machines

The analysis of complex biomedical datasets is becoming central to understanding disease mechanisms, aiding risk stratification and guiding patient ma...

Pulmonary tuberculosis prediction using CAD4TB artificial intelligence (computer-aided detection for tuberculosis) based on thoracic x-ray photos among Indonesian subjects in hospital

Tuberculosis remains a major global health concern, particularly in high-burden countries where early detection is essential but often limited by insu...

AI portal tract detection and characterisation for a regional analysis of steatosis and inflammation in MASLD, MASH, and AIH

Annotation of liver biopsies, for disease staging is increasingly aided by digital pathology, however existing systems do not quantify inflammation an...

Artificial Intelligence-based Diagnosis of Kaposi Sarcoma using Photographs in Dark-skinned Patients

Advanced-stage disease at the time of diagnosis, with resultant high mortality, is among the most urgent issues for HIV-related Kaposi sarcoma (KS) in...

Genus-level transfer learning of Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry data predicts antibiotic resistance with greater accuracy

Bacterial resistance, driven by excessive antibiotic use, has rendered many traditional antibiotics ineffective. Despite the advantages of applying ma...

Predicting Bacterial Vaginosis Development using Artificial Neural Networks

Bacterial vaginosis (BV) is a dysbiosis of the vaginal microbiome, characterized by the depletion of protective Lactobacillus spp. and overgrowth of a...

Measuring the growth of infectious disease modelling publications and their impact on policymaking: a Large Language Model-assisted bibliometric review

Infectious disease modelling (IDM) is increasingly being used to understand disease transmission and inform public health policy. However, its growth ...