Primary Care

Electrocardiogram-based deep learning enables scalable screening of transthyretin amyloid cardiomyopathy

Transthyretin amyloid cardiomyopathy (ATTR -CM) is a treatable but underrecognized cause of heart failure, with diagnosis often delayed until advanced disease manifests. This gap is amplified in underserved populations at increased risk for ATTR -CM where access to specialist evaluation and advanced cardiac imaging is limited. Electrocardiograms (ECGs) are ubiquitous and often obtained years befor...

Development and validation of a lesion-supervised deep learning system for diabetic retinopathy grading according to UK national screening criteria

Background: Diabetic retinopathy (DR) is the leading cause of preventable blindness among working-age adults worldwide, yet screening coverage remains inadequate, particularly in low- and middle-income countries. Automated deep learning systems offer potential to address the global shortage of expert graders, but most existing models lack lesion-level interpretability and are not aligned with esta...

Exposome-Based Clustering of Urinary VOC and PAH Biomarkers Reveals Racially Patterned Cardiovascular Risk in a Nationally Representative US Cohort: A Machine Learning Analysis of NHANES 2017-2018

Background Polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are combustion-derived pollutants linked to cardiovascular di...

Development of Explainable Machine Learning Framework for Early Detection and Risk Stratification of Diabetes in Age Specific Variations

Objective To develop and evaluate a novel machine learning (ML) framework tailored to a clinical diabetes dataset and to assess whether demographic st...

Generative Augmentation Reveals Previously Overlooked Signals in Transcriptomic Datasets

Identifying robust gene expression signatures from transcriptomic studies with small sample sizes remains one of the most persistent challenges in com...

An empirical evaluation of the risks of AI model updates using clinical data: stability, arbitrariness, and fairness

Artificial Intelligence and Machine Learning (AI/ML) models used in clinical settings are increasingly deployed to support clinical decision-making. H...

Impact of Age Specialized Models for Hypoglycemia Classification

Disease progression varies with age and is influenced by underlying genetic, biochemical, and hormonal etiologies, suggesting the need for tailored mo...

Patient perspectives on living with hypertension: Social media listening analysis across predominantly high-income countries

Background: Chronic conditions such as hypertension can significantly disrupt daily life and emotional wellbeing. The interaction between patients' pe...

Opportunistic Bone-Loss Screening from Routine Knee Radiographs Using a Multi-Task Deep Learning Framework with Sensitivity-Constrained Threshold Optimization

Background: Osteoporosis and osteopenia are often undiagnosed until fragility fractures occur. Dual-energy X-ray absorptiometry (DXA) is the reference...

Predictive Modeling of Natural Medicinal Compounds for Alzheimer Disease Using Cheminformatics

The most common cause of dementia is Alzheimer disease, a progressive neurodegenerative disorder affecting older adults that gradually impairs memory,...

SCOPE: Integrating Organoid Screening and Clinical Variables Through Machine Learning for Cancer Trial Outcome Prediction

BackgroundPredicting whether a treatment will demonstrate meaningful clinical benefit before committing to a large-scale trial remains a major unmet n...

Training-Free Cross-Lingual Dysarthria Severity Assessment via Phonological Subspace Analysis in Self-Supervised Speech Representations

Dysarthric speech severity assessment typically requires either trained clinicians or supervised machine learning models built from labelled pathologi...

Automated Detection of Dental Caries and Bone Loss on Periapical and Bitewing Radiographs using a YOLO Based Deep Learning Model

BackgroundDental caries and periodontal disease represent the most prevalent global oral health conditions, collectively affecting several billion peo...

PBE-UNet: A light weight Progressive Boundary-Enhanced U-Net with Scale-Aware Aggregation for Ultrasound Image Segmentation

Accurate lesion segmentation in ultrasound images is essential for preventive screening and clinical diagnosis, yet remains challenging due to low con...

Fundus Image-based Glaucoma Screening via Retinal Knowledge-Oriented Dynamic Multi-Level Feature Integration

Automated diagnosis based on color fundus photography is essential for large-scale glaucoma screening. However, existing deep learning models are typi...

LoGo-MR: Screening Breast MRI for Cancer Risk Prediction by Efficient Omni-Slice Modeling

Efficient and explainable breast cancer (BC) risk prediction is critical for large-scale population-based screening. Breast MRI provides functional in...

Decisions and Deployment: The Five-Year SAHELI Project (2020-2025) on Restless Multi-Armed Bandits for Improving Maternal and Child Health

Maternal and child health is a critical concern around the world. In many global health programs disseminating preventive care and health information,...

Cardiometabolic health trajectories from birth to old age based on multi-decadal series of biochemistry and anthropometry

Background and aims: Direct evidence to connect early life metabolism with cardiometabolic diseases in old age is limited due to the rarity of multi-d...

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-ba...

Temporally Phenotyping GLP-1RA Case Reports with Large Language Models: A Textual Time Series Corpus and Risk Modeling

Type 2 diabetes case reports describe complex clinical courses, but their timelines are often expressed in language that is difficult to reuse in long...