Primary Care

Latest AI and machine learning research in primary care for healthcare professionals.

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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 epidemiologi...

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 expres...

Managing Diabetic Retinopathy with Deep Learning: A Data Centric Overview

Diabetic Retinopathy (DR) is a serious microvascular complication of diabetes, and one of the leadin...

Evaluating the Large Language Model-Based Quality Assurance Tool for Auto-Contouring

Purpose: Manual verification of AI-based auto-contouring is labor-intensive and prone to fatigue-rel...

Aging Signals on Chest Radiographs: Association of Chest Radiograph-Derived Age Acceleration With Future Lung Cancer Incidence

Purpose: To evaluate whether chest radiograph-derived age acceleration is associated with incident l...

Screening for prostate cancer using PSA with and without MRI: systematic reviews with meta-analysis

Background: Previous recommendations on screening for prostate cancer relied on ongoing trials of sc...

Evolutionary exploration of drug-like chemical space utilizing generative AI and virtual screening

The identification of suitable lead molecules in the vast chemical space is a critical and challengi...

Retinal microvascular features are associated with CMR measures of subclinical cardiovascular dysfunction

Background Microvascular dysfunction is a key component of many cardiovascular (CV) diseases. Assess...

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 ...

Gap Safe Screening Rules for Fast Training of Robust Support Vector Machines under Feature Noise

Robust Support Vector Machines (R-SVMs) address feature noise by adopting a worst-case robust formul...

VOLMO: Versatile and Open Large Models for Ophthalmology

Vision impairment affects millions globally, and early detection is critical to preventing irreversi...

Brieflow: An Integrated Computational Pipeline for High-Throughput Analysis of Optical Pooled Screening Data

Optical pooled screening (OPS) has emerged as a powerful technique for functional genomics, enabling...

VOLMO: Versatile and Open Large Models for Ophthalmology

Vision impairment affects millions globally, and early detection is critical to preventing irreversi...

Continuous-Time Learning of Probability Distributions: A Case Study in a Digital Trial of Young Children with Type 1 Diabetes

Understanding how biomarker distributions evolve over time is a central challenge in digital health ...

SleepJEPA: Learning the latent world of sleep with at-home sleep data to estimate disease risk

Sleep disturbances lead to risk for cardiovascular (CV), metabolic, and neurological diseases. While...

Social Determinants of Health and Chronic Disease Risk Prediction in the All of Us Research Program

Social determinants of health (SDoH), the social, economic, and environmental conditions shaping hea...

Clinical Graph-Mediated Distillation for Unpaired MRI-to-CFI Hypertension Prediction

Retinal fundus imaging enables low-cost and scalable hypertension (HTN) screening, but HTN-related r...

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