Public Health & Policy

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 detection architectures and ordinal-aware supervision strategies perform under realistic post-disaster conditions. TornadoNet provides the first controlled benchmark demonstrating how architectural design and loss formulation jointly influence multi-level da...

Machine Unlearning for GDPR Right-to-Erasure in Antimicrobial Resistance Prediction Models

Objective. Healthcare machine learning models trained on patient data must comply with the General Data Protection Regulation (GDPR) right to erasure requirement, which mandates the removal of individual data contributions from deployed models. Full retraining, the current standard, is computationally expensive. This study evaluates Sharded, Isolated, Sliced, and Aggregated (SISA) training as an e...

Automated Segmentation of Intracranial Arteries on 4D Flow MRI for Hemodynamic Quantification

Accurate vessel segmentation is essential for reliable hemodynamic quantification in 4D Flow MRI. Automated segmentation with deep learning offers a p...

Condition-Specific Readmission Risk Stratification in a Predominantly Black Statewide Cohort Using Machine Learning: Development of Subtype-Specific Models for Heart Failure, Acute Myocardial Infarction, Atrial Fibrillation/Flutter, and Hypertensive Heart Disease

Background: Cardiovascular disease (CVD) readmissions impose substantial clinical and economic burden. Machine learning (ML) may improve risk stratifi...

AI-Driven Feature Selection Using Only Survey Variable Descriptions: Large Language Models Identify Adolescent Vaping Predictors

Objective: To evaluate the effectiveness of various Large Language Models (LLMs) in identifying reliable predictors of Electronic Nicotine Delivery Sy...

Sex-stratified Integrated Analysis of US lung Cancer Mortality, 1994-2020

Importance: Lung cancer mortality in the United States has fallen substantially in recent decades, yet the relative influence of behavioral, environme...

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 ...

Learning Optimal Individualized Decision Rules with Conditional Demographic Parity

Individualized decision rules (IDRs) have become increasingly prevalent in societal applications such as personalized marketing, healthcare, and publi...

Bridging Human Evaluation to Infrared and Visible Image Fusion

Infrared and visible image fusion (IVIF) integrates complementary modalities to enhance scene perception. Current methods predominantly focus on optim...

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...

Enhanced Insights into Alcohol Use Disorder from Lifestyle, Background, and Family History in a Large-Scale Machine Learning Study

Alcohol Use Disorder (AUD) is a multifactorial condition with severe individual and societal impacts. Extending our 2024 study, this work examines lif...

Bias in respiratory diagnoses by Large Language Models (LLMs) in Low Middle Income Countries (LMICs)

Introduction Clinicians and patients are likely to increasingly use Large Language Models (LLMs) for diagnostic support. Use of LLMs mostly created in...

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...

The Causal Impact of Natural Language Processing-Driven Clinical Decision Support on Sepsis Mortality in England: An Augmented Synthetic Control Analysis of NHS Trust-Level Data

Background: Sepsis remains a leading cause of preventable hospital mortality in England, with NHS England reporting over 48,000 sepsis-related deaths ...

Care Plan Generation for Underserved Patients Using Multi-Agent Language Models: Applying Nash Game Theory to Optimize Multiple Objectives

Background Clinicians in care management programs are often in low supply relative to patient demand, especially in US Medicaid programs, and must sim...

Breaking Semantic-Aware Watermarks via LLM-Guided Coherence-Preserving Semantic Injection

Generative images have proliferated on Web platforms in social media and online copyright distribution scenarios, and semantic watermarking has increa...

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...

Evaluating the AI Potential as a Safety Net for Diagnosis: A Novel Benchmark of Large Language Models in Correcting Diagnostic Errors

Background: Diagnostic errors are a leading cause of preventable patient harm, often occurring during early clinical encounters where diagnostic uncer...

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...