Primary Care

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

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Patient foundation model for risk stratification in low-risk overweight patients

Accurate risk stratification in patients with overweight or obesity is critical for guiding preventi...

Epistemic Throughput: Fundamental Limits of Attention-Constrained Inference

Recent generative and tool-using AI systems can surface a large volume of candidates at low marginal...

Machine Learning Phenotyping of Autonomic Stress from Daily Temperature and Ecological Assessments

Background: Artificial intelligence applications for preventive stress monitoring remain limited by ...

Assessing extracellular vesicle proteins as predictive biomarkers for developing type 1 diabetes

Plasma extracellular vesicles (EVs) are considered excellent sources for biomarker discovery since t...

AI-driven discovery and engineering of human endogenous nanocage proteins for mRNA delivery

Safe and effective gene delivery remains a central challenge for therapeutic applications. While non...

Altered Baseline Brain Network Topology in High-Risk Individuals Progressing to Mild Cognitive Impairment

Background: Identifying early brain-based markers of cognitive decline is critical for preventive st...

Personalised approach to hypertension treatment: Rationale and design of the HYPERMARKER randomised trial

Background and Objective: Blood pressure treatment response is variable in individual patients, and ...

Aortic Valve Disease Detection from PPG via Physiology-Informed Self-Supervised Learning

Traditional diagnosis of aortic valve disease relies on echocardiography, but its cost and required ...

Deep Learning-Enabled Screening of Chronic Kidney Disease from Echocardiography

Chronic kidney disease (CKD) affects nearly 850 million individuals globally; the prevalence of undi...

Full end-to-end diagnostic workflow automation of 3D OCT via foundation model-driven AI for retinal diseases

Optical coherence tomography (OCT) has revolutionized retinal disease diagnosis with its high-resolu...

BlueNuclei: automated identification and classification of live and dead transfected neurons using interpretable features

In vitro modeling of neuronal disorders using transfected primary neurons is one of the fundamental ...

Generation of Synthetic Data in Health Surveys Using Large Language Models

Background: Generating synthetic data using artificial intelligence, such as large language models (...

Exploring Attitudes and Acceptance of Artificial Intelligence in Multiple Sclerosis from the Patient Perspective

Artificial intelligence (AI) is increasingly being integrated into healthcare, particularly in data-...

Privacy-Preserving Sensor-Based Human Activity Recognition for Low-Resource Healthcare Using Classical Machine Learning

Limited access to medical infrastructure forces elderly and vulnerable patients to rely on home-base...

Glance and Focus Reinforcement for Pan-cancer Screening

Pan-cancer screening in large-scale CT scans remains challenging for existing AI methods, primarily ...

Time-to-Injury Forecasting in Elite Female Football: A DeepHit Survival Approach

Injury occurrence in football poses significant challenges for athletes and teams, carrying personal...

Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data

Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels due to impai...

RareAlert: Aligning heterogeneous large language model reasoning for early rare disease risk screening

Missed and delayed diagnosis remains a major challenge in rare disease care. At the initial clinical...

Fair-Eye Net: A Fair, Trustworthy, Multimodal Integrated Glaucoma Full Chain AI System

Glaucoma is a top cause of irreversible blindness globally, making early detection and longitudinal ...

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