Infectious Disease

A comparative analysis of dengue, chikungunya, and Zika in a pediatric cohort over 18 years

Dengue, chikungunya, and Zika are diseases of major human concern. Differential diagnosis is complicated in children and adolescents by their overlapping clinical features (signs, symptoms, and complete blood count results). Few studies have directly compared the three diseases. We aimed to identify distinguishing pediatric characteristics of each disease. Data were derived from laboratory-confirm...

STM-GNN: Space-Time-and-Memory Graph Neural Networks for Predicting Multi-Drug Resistance Risks in Dynamic Patient Networks

Hospital-acquired infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria, pose significant risks to vulnerable patients. Accurate predictive models are important for assessing infection dynamics and informing infection prediction and control (IPC) programmes. Graph-based methods, including graph neural networks (GNNs), offer a powerful approach to model complex relation...

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 ...

Outbreak and Postnatal Antibiotic Exposures Drive the Development Trajectory of the Nasopharyngeal Microbiota in the First Year of Life

Early exposure to antibiotics and prolonged hospitalization in preterm infants may perturb microbiome development and contribute to adverse health out...

AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, their overall impact on the health of older adults r...

Dengue forecasting and outbreak detection in Brazil using LSTM: integrating human mobility and climate factors

Dengue fever is a major global health concern, with Brazil experiencing recurrent and severe outbreaks due to its favorable climate factors, socio-env...

Mapping Inequities in Global Vaccine Sentiment Research

Negative public sentiment towards vaccination (PSV) poses significant challenges to the effectiveness of immunization programs, with dramatic effects ...

Deep learning-based localization of bounded edentulous spaces in intraoral occlusal images

This study developed a deep learning pipeline to localize bounded edentulous spaces with missing teeth FDI number directly from intraoral photographs,...

COVID-19 modulates pregnancy outcomes

The COVID-19 pandemic exposed many pregnant individuals to SARS-CoV-2. Literature suggests a link between gestational COVID-19 and adverse gestational...

Exploring Novel Kinetics of Automated H2O2 Nebulization: A Breakthrough in SARS-CoV-2 Elimination

Although hydrogen peroxide (H2O2) nebulization has shown promise for reducing SARS-CoV-2 loads in healthcare settings, its precise kinetics and real-w...

Predicting clinical outcome of Escherichia coli O157:H7 infections using explainable Machine Learning

Shiga toxin-producing Escherichia coli (STEC) O157:H7 is a globally dispersed zoonotic pathogen capable of causing severe disease outcomes, including ...

Urinary collagen peptides predict mortality

Organ fibrosis caused by the presence of excessive extracellular matrix (ECM) is strongly related to mortality. Urinary peptide signatures were report...

Diagnostic accuracy of a high-throughput multiplex immunoassay for the detection of Mpox virus infection and MVA-BN vaccination up to two years after exposure

Mpox, caused by mpox virus (MPXV), has gained global attention following the 2022 Clade IIb outbreak and the emergence of two novel Clade I lineages i...

Nucleotide motif-guided selection of plasma microRNA biomarkers for organ injury prediction in trauma

Trauma remains a leading cause of morbidity and mortality in part due to secondary organ injury and infection. Yet, our ability to predict the downstr...

Advancing the Safe Motherhood Initiative: a qualitative and sentiment analysis of local physician’s perspectives on antibiotic self-medication during pregnancy in a low- and middle-income country

Although the Safe Motherhood Initiative is currently a global priority, the implications of maternal self-medication for meeting Safe Motherhood and S...

Granular Insights:A Wastewater-Based Machine Learning Approach for Localized COVID-19 Hospitalization Forecasting

Wastewater based epidemiology (WBE) is a valuable tool for monitoring emerging disease trends in a community. Specifically, early predictions of hospi...

Enhancing Pandemic Prediction: A Deep Learning Approach Using Transformer Neural Networks and Multi-Source Data Fusion for Infectious Disease Forecasting

The Covid-19 pandemic has highlighted the urgent need for accurate prediction of pandemic trends. We propose a deep learning model for predicting Covi...

M-PreSS: A Model Pre-training Approach for Study Screening in Systematic Reviews

Conducting a systematic review is labour-intensive and time-consuming, especially during the study screening process. Previous research has introduced...

Evaluation of the Bangkok Health Research and Ethics Interest Group: reflecting on the experiences of group members, researchers and facilitators participating in an urban community advisory board in Thailand

The Mahidol Oxford Tropical Medicine Research Unit (MORU), headquartered in Bangkok, conducts research on tropical medicine and global health. MORU wo...

Evaluation of a real time machine learning sepsis risk algorithm for Emergency Department waiting rooms (SAFE-WAIT)

To evaluate and compare the real-time Sepsis risk Artificial intelligence algorithm For Emergency department WAITing room (SAFE-WAIT) model with the s...