Public Health & Policy

Latest AI and machine learning research in public health & policy for healthcare professionals.

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High-Performance Classification of Mpox Symptoms Using Support Vector Classifier and Quadratic Discriminant Analysis

Background: Recent global outbreaks of Mpox have posed significant diagnostic challenges, particularly in resource-limited settings. Conventional diagnostic methods are often inaccessible due to cost, logistical constraints, or lack of trained personnel. These limitations highlight the urgent need for alternative, scalable diagnostic strategies. This study explored the application of machine learn...

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 specialized bioinformatics expertise and manual interpretation, creating substantial bottlenecks in time-sensitive diagnostic settings. The key challenges lie in achieving precise species identification amidst high background noise and translating c...

(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...

The Sound of Death: Deep Learning Reveals Vascular Damage from Carotid Ultrasound

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, yet early risk detection is often limited by available diagnostics. Ca...

Feb 19 2026 2602.17321v1
Disparities, Perceived Discrimination, and Patient-Clinician Communication in Alcohol Use Disorder Treatment: An All of Us Cohort Study

Background and Aims: Alcohol use disorder (AUD) remains a major public health concern, with persistent disparities in access to evidence-based treatme...

Insulin resistance modifies longitudinal multi-omics responses to habitual diet

How habitual diet influences the gut microbiome and plasma metabolome across insulin resistance states remains unclear. We conducted year-long multi-o...

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...

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...

Feb 16 2026 2602.14989v1
Patterns of preventable death and government response compliance across Australian coronial jurisdictions: a natural language processing analysis of 9833 findings

ABSTRACT Objectives: To quantify patterns of preventable death in Australian coronial findings, measure government compliance with coroner recommendat...

Inferring unobserved vector dynamics for dengue forecasting using physics-informed neural networks and mechanistic transmission models

Accurately characterising mosquito infection dynamics is essential for effective dengue prevention and control, yet these dynamics are rarely observab...

Data-Driven Multimodal Subtyping Reveals Differential Cognitive Risk and Treatment Effects in the All of Us Cohort

INTRODUCTION: Cognitively unimpaired (CU) adults show substantial variation in their risk of developing mild cognitive impairment (MCI), yet most subt...

Wastewater-informed neural compartmental model for long-horizon case number projections

Wastewater-based epidemiology provides a low-cost, scalable view of community infection dynamics, but converting these signals into actionable epidemi...

One-Shot Crowd Counting With Density Guidance For Scene Adaptaion

Crowd scenes captured by cameras at different locations vary greatly, and existing crowd models have limited generalization for unseen surveillance sc...

Feb 8 2026 2602.07955v1
An AI Agent for Automated Causal Inference in Epidemiology

Abstract Objective: To address the inefficiency, subjectivity, and high expertise barrier of traditional epidemiological causal inference, this study ...

[Advances in frontier technologies and innovative applications for the prevention and control of hospital infections associated with multidrug-resistant bacteria].

Hospital-acquired infections (HAIs) significantly increase patient mortality and healthcare burden, with multidrug-resistant organisms (MDROs) exacerb...

Feb 6 2026 41606984
Predictive Modeling of COVID-19 Variant Peak Prevalence and Duration Using GISAID Data Across 15 Countries

BackgroundRapid emergence and replacement of SARS-CoV-2 variants underscore the need for early and reliable indicators of variant dominance to guide t...

Unseen Insights: An AI-Powered Exploration of Secure Patient Messages in Ophthalmology

Objective To characterize the clinical and administrative concerns communicated through secure ophthalmology messaging and to assess differences in me...

Deep Lipidomic Phenotyping Identifies Ceramide-Centered Lipotoxicity and Depletion of Plasmalogen-Carnitine Pathways in Major Depressive Disorder: Implications for Precision Medicine

Background: Major depressive disorder (MDD) severely impairs individual health and creates heavy societal burdens. Diagnostic and therapeutic research...

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