Public Health

Toward Unified Fine-Grained Vehicle Classification and Automatic License Plate Recognition

Extracting vehicle information from surveillance images is essential for intelligent transportation systems, enabling applications such as traffic monitoring and criminal investigations. While Automatic License Plate Recognition (ALPR) is widely used, Fine-Grained Vehicle Classification (FGVC) offers a complementary approach by identifying vehicles based on attributes such as color, make, model, a...

TELF: An End-to-End Temporal Encoder with Late Fusion for Interpretable Disease Risk Prediction from Longitudinal Real-World Data

Deep learning models utilizing longitudinal healthcare data have significantly advanced epidemiological research. However, contemporary transformer-based models increasingly rely on computationally intensive pre-training steps that entail processing massive real-world datasets with cost-prohibitive hardware. We introduce the Temporal Encoder with Late Fusion (TELF), a lightweight end-to-end predic...

Predicting COVID-19 incidence from seroprevalence and population-based cohort data using interpretable machine learning with differential privacy analysis

During the COVID-19 pandemic, reported incidence data played a central role in public health surveillance and in tracking epidemic dynamics, although ...

Predicting highly pathogenic avian influenza H5N1 outbreak risk using extreme weather and bird migration data in machine learning models

Background. Climate change is intensifying extreme weather events (EWEs) with potentially profound consequences for zoonotic disease dynamics, yet the...

MedResearchBench: A Multi-Domain Benchmark for Evaluating AI Research Agents on Clinical Medical Research

The rapid advancement of AI research automation systems--including AI Scientist, data-to-paper, and Agent Laboratory--has demonstrated the potential f...

Deciphering Environmental Health Factors Behind Unknown Etiology of Chronic Kidney Disease in South Asia: Plans for Epidemiologic Study

Chronic kidney disease of unknown etiology (CKDu) has emerged as an important public health challenge, particularly in agricultural communities across...

faers: A High-Fidelity Framework and R/Bioconductor Package for Precision Adverse Event Surveillance

Background: The FDA Adverse Event Reporting System (FAERS) is a critical pillar of post-marketing pharmacovigilance; however, its utility is constrain...

Classification of Recurrence Status After Surgical Treatment of Chronic Subdural Hemorrhage - A Machine Learning Approach

Background Chronic subdural hematoma (cSDH) recurrence requiring reoperation occurs in 5-33% of cases, representing a substantial clinical and economi...

Predicting Infant Nonattendance at the Next Recommended Well-Child Visit: Model Development and Validation

BackgroundWell-child visits (WCVs) are essential for preventive care, yet missed appointments often lead to delayed interventions. We developed and va...

Development of a natural language processing application to extract and categorize mentions of violence from mental healthcare records text

Background: Experiences of violence are reported frequently by mental health service users, victims of violence are at a greater risk of mental health...

SDD-YOLO: A Small-Target Detection Framework for Ground-to-Air Anti-UAV Surveillance with Edge-Efficient Deployment

Detecting small unmanned aerial vehicles (UAVs) from a ground-to-air (G2A) perspective presents significant challenges, including extremely low pixel ...

Learning relationships in epidemiological data using graph neural networks

When designing control strategies for an infectious disease it is critical to identify the key pathways of transmission. Data on infected hosts - when...

Resolving gradient pathology in physics-informed epidemiological models

Physics-informed neural networks (PINNs) are increasingly used in mathematical epidemiology to bridge the gap between noisy clinical data and compartm...

Climate-Informed Deep Learning for Spatio-Temporal Forecasting of Climate-Sensitive Diseases

Effective public health planning and intervention strategies necessitate an understanding of the temporal and geographic distribution of disease incid...

ForeSea: AI Forensic Search with Multi-modal Queries for Video Surveillance

Despite decades of work, surveillance still struggles to find specific targets across long, multi-camera video. Prior methods -- tracking pipelines, C...

Predictive and Seasonal Dynamics of the Human Wastewater Virome

Wastewater-based epidemiology provides a scalable, noninvasive framework for population-level infectious disease monitoring, but traditional assays li...

PRIME-CVD: A Parametrically Rendered Informatics Medical Environment for Education in Cardiovascular Risk Modelling

In recent years, progress in medical informatics and machine learning has been accelerated by the availability of openly accessible benchmark datasets...

A Machine Learning Approach to Defining and Predicting the Scale of Typhoid Fever Outbreaks

Despite improvements in access to clean water and sanitation, typhoid fever outbreaks continue to cause substantial morbidity and mortality worldwide....

Ancestral state reconstruction with discrete characters using deep learning

Ancestral state reconstruction is a classical problem of broad relevance in phylogenetics. Likelihood-based methods for reconstructing ancestral state...

HViLM: A Foundation Model for Viral Genomics Enables Multi-Task Prediction of Pathogenicity, Transmissibility, and Host Tropism

Motivation: The emergence of novel viral pathogens poses critical threats to global health, yet current computational approaches for viral risk assess...