Public Health

Spatiotemporal Patterns and Climate-Driven Forecasting of Scrub Typhus: Evidence from South India.

Scrub typhus remains a persistent public health concern with strong spatial and temporal variability. This study analyses the spatio-temporal distribution, clustering patterns, and forecasting of scrub typhus across five districts, Chittoor, Ranipet, Tirupattur, Vellore, and Tiruvannamalai, using long-term surveillance data from May 2005 to May 2024. We applied spatio-temporal exploratory analysis...

A Machine Learning Framework for Constructing Heterogeneous Contact Networks: Implications for Epidemic Modelling

Capturing the structured mixing within a population is key to the reliable projection of infectious disease dynamics and hence informed control. Both heterogeneity in the number of epidemiologically-relevant contacts and age-structured mixing have been repeatedly demonstrated as fundamental, yet are rarely combined. Networks provide a powerful and intuitive method to realise these two elements of ...

Comparative Evaluation of Logistic Regression and Gradient Boosting Models for Influenza Outbreak Early-Warning Using U.S. CDC ILINet Surveillance Data (2010-2025)

Background Timely detection of seasonal influenza outbreaks is critical for healthcare system preparedness and public health response. Although numero...

Antenatal surveillance of placental function using a wearable near infrared spectroscopy device with machine learning data interpretation

Background Placental dysfunction remains a leading cause of stillbirth and neonatal morbidity, yet current monitoring tools provide only indirect and ...

TornadoNet: Real-Time Building Damage Detection with Ordinal Supervision

We present TornadoNet, a comprehensive benchmark for automated street-level building damage assessment evaluating how modern real-time object detectio...

A Machine Learning Framework for Serogroup Classification of pathogenic species of Leptospira Based on rfb Locus Profiles

Leptospira is a highly diverse genus traditionally classified by serological assays into more than 30 serogroups and over 300 serovars. However, this ...

A multi-center analysis of deep learning methods for video polyp detection and segmentation

Colonic polyps are well-recognized precursors to colorectal cancer (CRC), typically detected during colonoscopy. However, the variability in appearanc...

Multistate Animal-Contact-Related Nontyphoidal Salmonella enterica Outbreaks in the United States, 2009-2022: Network and Machine Learning Analyses of Exposure Sources, Settings, and Serovars

Background: Nontyphoidal Salmonella enterica (NTS) is a major public-health threat in the United States of America (U.S.). Evaluating associations bet...

Leveraging large language models to address common vaccination myths and misconceptions

Large language models (LLMs) are increasingly used by the public to seek health information, yet their reliability in addressing common vaccine myths ...

t2pmhc: A Structure-Informed Graph Neural Network to predict TCR-pMHC Binding

Mapping of T cell receptors (TCRs) to their cognate MHC-presented peptides (pMHC) is central for the development of precision immunotherapies and vacc...

Evaluation of six different tests for Schistosoma haematobium diagnosis in a near-elimination setting: a prospective observational diagnostic accuracy study

Background Accurate diagnostic tools are needed in schistosomiasis elimination settings to determine prevalence thresholds for assigning or stopping i...

Data-Driven Hybrid Model of SARIMA-CNNAR For Tuberculosis Incidence Time Series Analysis in Nepal

Abstract Background Tuberculosis (TB) remains a major public health challenge in Nepal, with incidence rates substantially higher than global estimate...

Automated Model Discovery Based on COVID-19 Epidemiologic Data

The COVID-19 pandemic has presented severe challenges in understanding and predicting the spread of infectious diseases, necessitating innovative appr...

Genomic Evolution of SARS-CoV-2 Delta Variants Pre- and Post-Omicron Emergence using Alignment-free Machine Learning models

The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutatio...

GPAS: an online AI system for rapid and accurate pathogen identification and LLM-based interpretation

Accurate identification of unknown pathogens is critical for medicine and public health, yet current metagenomic workflows remain heavily dependent on...

(How) Do Health Shocks Reallocate Research Direction?

We examine whether research systems reallocate scientific effort as health needs change. We assemble a global disease-location panel for 204 countries...

A multi-layered approach to elucidate mechanisms of physical function in response to rehabilitation in heart failure with preserved ejection fraction

Heart failure with preserved ejection fraction (HFpEF) is an increasingly common cause of morbidity and mortality in older adults that is driven by ca...

Machine learning-based framework for predicting human infection potential of coronavirus associated with tri-amino acid motifs, KIQ and LEP in spike protein

Assessing the human infection potential of emerging coronaviruses remains a critical challenge for global health preparedness. In this study, we devel...

Universal Image Immunization against Diffusion-based Image Editing via Semantic Injection

Recent advances in diffusion models have enabled powerful image editing capabilities guided by natural language prompts, unlocking new creative possib...

ThermEval: A Structured Benchmark for Evaluation of Vision-Language Models on Thermal Imagery

Vision language models (VLMs) achieve strong performance on RGB imagery, but they do not generalize to thermal images. Thermal sensing plays a critica...