Primary Care

Enhancing Competencies of Nursing Students in Pain Management Education Through Artificial Intelligence (AI): A Narrative Review.

BACKGROUND: Effective pain management is a vital aspect of quality nursing care, requiring sound knowledge, assessment skills, clinical judgment, and patient-centered communication. With advances in healthcare technology, Artificial Intelligence (AI) is emerging as a powerful educational tool to enhance competency-based learning in pain management. OBJECTIVES: This narrative review explores how AI...

Automotive Health 2.0: Steering Toward Proactive Preventive Care.

Cardiovascular and chronic disease prevention remains limited by episodic, clinic-based assessments that fail to capture physiological changes arising in daily life. As mobility constitutes one of the most stable and repetitive environments people inhabit, vehicles offer a unique setting for subliminal, continuous health monitoring. This narrative presents the rationale and foundational framework ...

Revolutionizing salivary biomarkers through machine learning and artificial intelligence.

Chronic diseases remain major global health burdens, and early detection is essential for preventing progression and reducing complications. Saliva, a...

Protector role of muscle quality against diabetes in non-elderly U.S. adults.

BACKGROUND: Since 1980, the number of people with diabetes has doubled globally, a figure expected to reach 783 million by 2045. The Muscle Quality In...

A Systematic Review on Applications of Artificial Intelligence for Obesity Prevention.

This systematic review examines the applications of artificial intelligence (AI) in preventing obesity, addressing a critical public health issue that...

Estimating the effect of reducing average annual ambient PM2.5 concentrations on allostatic load in children.

OBJECTIVE: Chronic exposure to environmental stressors may result in dysregulation across the body's adaptive stress-response systems, which can be co...

Visceral Adipose Tissue Alters Podometrics and Renal Compensation After Uninephrectomy.

INTRODUCTION: Obesity is an established risk factor for chronic kidney disease (CKD). However, excess visceral adipose tissue (VAT) termed visceral ob...

Machine learning-based prediction of large-for-gestational-age neonates in diabetic and non-diabetic pregnancies.

OBJECTIVE: This study determines whether a machine-learning model integrating sonographic biometry with maternal clinical parameters improves predicti...

An Unsupervised Learning Approach for Multimodal Low Back Pain Stratification.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study proposes a novel stratification framework for individuals with low back pain (LBP). The met...

Relationship between cardiometabolic index and worsening renal function in T2DM: Insights from machine learning, growth mixture modelling, and development of a web-based risk prediction tool.

AIM: Worsening renal function (WRF) is a common and serious complication of type 2 diabetes mellitus (T2DM), contributing to adverse clinical outcomes...

Breaking resistance with machine and deep learning: A computational intelligence hunt for AmvR (TetR) inhibitors in Acinetobacterbaumannii.

Multidrug-resistant Acinetobacter baumannii infections have driven the development of innovative therapeutic approaches to address global challenges. ...

Performance of large language models in addressing patient queries on colorectal cancer screening in different languages: An international study across 28 countries.

BACKGROUND: Colorectal cancer (CRC) screening reduces incidence and mortality, yet patient adherence remains suboptimal. Large language models may imp...

The micro- and nanoplastics exposome feedback loop drives synergistic air-lung toxicity.

Airborne micro- and nanoplastics (MNPs) are now recognized as persistent components of the atmospheric exposome. While their presence is established, ...

Strategizing AI utilization for psychological literature screening: A comparative analysis of machine learning algorithms and key factors to consider.

With the rapid growth of scholarly literature, efficient artificial intelligence (AI)-aided abstract screening tools are becoming increasingly importa...

Screening for depressive symptoms in primary and secondary school students based on speech features: A one-year longitudinal study from Jiangsu, China.

OBJECTIVE: This study aims to develop and validate an interpretable prediction model for recognizing depression risk in primary and secondary school s...

The use of large language models in clinical documentation: A scoping review.

BACKGROUND: Clinical documentation is essential for safe, high-quality care but has become increasingly complex, contributing to clinician burnout. La...

Advances in occult cancer screening for patients with unprovoked venous thromboembolism: A narrative review of epidemiology, risk, and clinical strategies.

BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...

Targeting High-Risk Populations for Abdominal Aortic Aneurysm Screening: A Sex-Stratified Analysis in an Ethnicity Diverse Cohort Incorporating Machine Learning Tools.

BACKGROUND: Abdominal aortic aneurysm (AAA) is usually asymptomatic, but rupture carries up to 90% mortality. Ultrasound screening reduces rupture-rel...

Differential factor effects in comorbid depressive and anxiety symptoms (CDAS): A machine learning approach to individualized mental health promotion.

BACKGROUND: Depression and anxiety comorbid presents greater severity than isolated symptoms. Traditional analyses often fail to capture complex inter...

The scope of cardiology research: More than 300 topics covered through bibliometric evaluation.

This study provides a bibliometric overview of cardiovascular-related bibliometric research identified in the Scopus database using a title-abstract-k...