Latest AI and machine learning research in primary care for healthcare professionals.
Sleep disorders are prevalent and constitute a major concern in patients with diabetes mellitus. Therefore, the aim of this study was to investigate the applicability of machine learning methods in predicting sleep disorders among diabetic patients. Six relevant features were selected using single-factor correlation analysis and the LASSO algorithm. We developed and evaluated five ML models: logis...
BACKGROUND: Personalized medicine, driven by genomic insights, has catalyzed the emergence of innovative clinical trial designs such as basket and umbrella trials. These designs are particularly suited for evaluating targeted therapies in biomarker-defined subgroups and rare pediatric conditions where traditional trials face challenges of small sample sizes and disease heterogeneity. OBJECTIVES: T...
BACKGROUND: Depression poses a severe public health challenge for older adults, especially in rural China. In rural settings, the heavy burden of chro...
BACKGROUND: Title and abstract screening is a labor-intensive stage of systematic reviews. Large language models (LLMs) can automate this process, but...
Opportunistic screening leverages existing imaging examinations performed for unrelated routine clinical indications to systematically extract quantit...
BACKGROUND: Obesity is the largest risk factor for endometrial cancer. Body Mass Index (BMI) does not fully capture obesity's metabolic and inflammato...
Fundus imaging enables noninvasive, high-resolution visualization of the retinal microvasculature. Advances in artificial intelligence (AI) now allow ...
OBJECTIVES: To identify the biological, behavioural, and socio-demographic determinants of childhood and adolescent obesity and evaluate how their rel...
Spinal cord injury (SCI) is a highly disabling central nervous system disease with complex pathology, and targeted neuroprotective drugs remain clinic...
OBJECTIVES: Computed tomography (CT) scans for lung cancer screening provide the opportunity of quantifying incidental findings. We evaluated the repe...
Disruptive technologies can reconfigure innovation trajectories and create new market opportunities, yet their early detection remains difficult becau...
Histologically stained tissue sections are considered the gold standard for studying microscopic anatomy and diagnosing disease in clinical practice. ...
BACKGROUND: Adolescent idiopathic scoliosis (AIS) affects 2-3% of adolescents. Current screening relies on X-rays, which limits large-scale applicatio...
AIMS: To validate behavioural subtypes among young and middle-aged hypertensive patients using latent class analysis (LCA) and assess their generaliza...
AIMS: Social isolation (SI) is associated with a higher risk of cardiovascular disease (CVD). One mechanism linking SI and CVD is accelerated biologic...
PURPOSE: To develop a deep learning model based on nnU-Net for automated segmentation of all perigastric veins on contrast-enhanced CT images in patie...
BACKGROUND: Lung cancer remains the leading cause of cancer deaths in the United States; however, uptake of lung cancer screening (LCS) with low-dose ...
OBJECTIVE: To validate the diagnostic accuracy of ICDAS visual examination, conventional bitewing radiography, and artificial intelligence (AI)-assist...
BACKGROUND: Online health information seeking (OHIS) has become a central component of chronic disease management within an increasingly interactive, ...
OBJECTIVE: Swallowing dysfunction poses significant health risks for older adults. Early detection is crucial to prevent complications such as aspirat...