Primary Care

Ligustilide and tectoridin from Danggui Buxue Decoction synergistically attenuate atherosclerosis by targeting the CD36/TRPM2 axis and TNF-α/NF-κB pathway.

BACKGROUND: Atherosclerosis (AS) is a common chronic disease and the primary pathological basis for myocardial infarction, stroke, and other disabling conditions. Danggui Buxue Decoction (DBD) is a classic formula in Traditional Chinese Medicine (TCM) normally used for deficiency patterns. However, whether DBD can alleviate atherosclerosis, which bioactive constituents are responsible, and which m...

Enhanced diabetic retinopathy detection via multimodal fusion of fundus imaging features and clinical demographic information using verifiable convolutional neural network.

Traditional systems of ocular disease diagnosis and many deep learning-based systems are limited in their practice to analyzing fundus images from a single eye, often using raw, unprocessed data. This fails to include the critical correlation between bilateral eyes, has several issues such as low image contrast, noise, and class imbalance, and generally concentrates on the detection of no more tha...

Transformative role of AI in primary care: What does it take to control hypertension?

Organ-on-chip bridging musculoskeletal disease modeling and precision therapeutic discovery.

Musculoskeletal (MSK) disorders remain a leading cause of disability, yet effective disease-modifying therapies are limited by poor translational rele...

Machine Learning-Based Risk Stratification Tool for Hearing Loss in High-Risk Neonates.

OBJECTIVE: This study aims to develop and evaluate a machine learning-based risk stratification tool for predicting hearing loss in high-risk neonates...

Development and Validation of an Interpretable Machine Learning Model for Predicting In-Hospital Mortality in Diabetic Patients with Sepsis-Associated Acute Kidney Injury.

BackgroundSepsis-associated acute kidney injury (SA-AKI) is a common and severe complication in critically ill patients, with poor prognosis. Diabetes...

iDCF: Interpretable deconvolution of cell fractions via biologically-informed deep learning using scRNA-seq data.

Precise resolution of cellular heterogeneity within complex tissues is fundamental to deciphering disease etiologies from bulk transcriptomic profiles...

A clinical decision support tool for accurate hip fracture prediction: A nationwide cohort study.

BACKGROUND: Although hip fractures are commonly associated with functional decline, increased morbidity, and mortality, accurate models for both short...

Artificial intelligence for healthcare in Nepal: A scoping review of clinical applications, implementation evidence, and health-system governance.

BACKGROUND: Nepal offers a distinctive LMIC setting for evaluating AI-health adoption due to its difficult geography, specialist shortage, high case b...

Artificial Intelligence and Machine Learning for Identifying Social Determinants of Health in Low-Income Populations Within United States Health Systems: A Scoping Review.

BACKGROUND AND AIMS: Low-income populations in the United States experience disproportionate exposure to adverse social conditions. This scoping revie...

A Two-Stage Hybrid Feature Selection and Ensemble Learning Framework With Explainable AI for Accurate PCOS Prediction.

BACKGROUND AND AIMS: Polycystic ovary syndrome (PCOS) is the most prevalent endocrine ailment impacting women of reproductive age, distinguished by on...

A narrative review of what cohorts have taught us and how they have laid the foundation for much of our understanding of type 2 diabetes.

This narrative review provides a historical perspective on how observational research on type 2 diabetes has been developed and consolidated over the ...

AI performance varies considerably across mammography devices: a multi-site and multi-vendor retrospective study.

OBJECTIVES: To evaluate an artificial intelligence (AI) algorithm on three different mammography devices and assess screening performance using genera...

Machine Learning Model Development and Evaluation for Non-contact Lower Limb Injury Risk Prediction in Elite Male Rugby Union: A Multi-team, Multi-season Analysis.

BACKGROUND: The prevalence, incidence rate and burden of injuries are high in rugby union. Despite the growing application of machine learning for inj...

AI Adoption in US Cancer Centers: National Cross-Sectional Study of Institutional and Policy Determinants.

BACKGROUND: AI is increasingly being integrated into cancer screening, treatment, and patient care. However, AI adoption across cancer centers varies,...

Diagnostic Performance of Deep Learning Using Retinal Images for Detection of Chronic Kidney Disease: A Systematic Review and Meta-analysis.

BACKGROUND: Multiple investigations have been conducted to diagnose chronic kidney disease (CKD) from photographs of retina using deep learning models...

A novel approach for liver steatosis assessment in ultrasound images using an adapted Vision-Language Foundation Model.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is among the most prevalent chronic liver diseases worldwide. B-mode ultrasound remai...

Artificial intelligence for risk prediction in atherosclerotic cardiovascular disease: A narrative review of advances, validation challenges, and clinical translation (2020-2026).

Since 2020, artificial intelligence (AI) has been increasingly applied to atherosclerotic cardiovascular disease (ASCVD) risk prediction. This structu...

Development and validation of a generalizable M-protein screening model using routine laboratory indicators: a multicenter retrospective study.

BACKGROUND: Early detection of plasma cell disorders (PCDs) remains challenging due to limited accessibility of gold standard diagnostic methods. This...

Automated AI quantification of retinal parameters associated with axial length progression in children: a cohort study.

PURPOSE: This study investigated whether quantitative retinal parameters derived from colour fundus photography are associated with axial length (AL) ...