Prevention

Improving 10-year cardiovascular disease risk prediction using automated machine learning.

AIMS: To develop a cardiovascular disease (CVD) risk prediction model with improved accuracy and interpretability by integrating diverse risk factors and applying Automated Machine Learning (AutoML), thereby enhancing clinical utility over conventional models. METHODS: This is a prospective cohort study. Data were obtained from the Multi-Ethnic Study of Atherosclerosis (MESA), including baseline a...

A comparative evaluation of ChatGPT-assisted and traditional methods of teaching diagnostic assessments to medical students: A randomized controlled study.

The rapid development of artificial intelligence (AI) technology has brought new opportunities and challenges to the ever-evolving field of medical education. However, the specific impact of AI on the teaching of diagnostic assessments to medical students requires further investigation. The purpose of this study was to evaluate the effectiveness of ChatGPT-assisted teaching of diagnoses. Eighty me...

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, ea...

Association Between the Dietary Inflammatory Index and Cardiorenal Anemia Syndrome: Evidence From NHANES and Related-Phenotype Exploration in KNHANES.

Cardiorenal anemia syndrome (CRAS) links heart failure, chronic kidney disease, and anemia, but the role of diet-related inflammation remains unclear....

Use of artificial intelligence in the peer review process of sports and exercise medicine research.

Trusting the Algorithm or Trusting the Nurse? Critical Care Nurses' Experiences of Automation Bias and Professional Autonomy in AI-Assisted Early Warning.

BACKGROUND: Artificial intelligence-assisted early warning systems (AI-EWS) are increasingly integrated into critical care, yet little is known about ...

Humanoid Colleagues and the Rheumatology Workforce: Preparing for a New Era.

Rheumatology faces sustained workforce strain, widening access gaps, and escalating administrative burden. Fellowship expansion and integration of adv...

Cross-tissue immune profiling of APOE ε4 reveals early dysregulation in Alzheimer's disease.

INTRODUCTION: Apolipoprotein E (APOE) ε4 is the strongest genetic risk factor for late-onset Alzheimer's disease (AD), but its contribution to disease...

A cross-species drug-discovery platform to accelerate the identification of lifespan-extending interventions.

We develop an integrated, high-throughput platform to evaluate pharmacological lifespan-extending interventions across five model organisms spanning u...

Transforming tai ji quan into next-generation, evidence-based exercise medicine: A translational roadmap for falls prevention.

A substantial body of research provides compelling evidence that tai ji quan, a mind-body exercise rooted in traditional Chinese medicine, is effectiv...

Technology and Obesity: A Year in Review.

SMART technological advancements help diagnose, treat, and monitor various diseases at the earliest stages. It presents an opportunity to maintain the...

Ai-based multimodal analysis of ECG and clinical data for evaluation for competitive sports participation: The VALETUDO trial.

AIMS: Pre-participation cardiovascular screening (PPS) is essential for preventing SCD in athletes, yet ECG interpretation requires expertise and rema...

Recent advances and knowledge gaps in anticoagulation strategy with durable left ventricular assist devices.

Driven by technological advancements, donor shortages, and an aging population, utilization of left ventricular assist devices (LVAD), both as a bridg...

ShenNongDiet: a medicine diet recommendation system based on graph-semantic hybrid retrieval and evidence constraint generation.

BACKGROUND: Medicinal diet, a core practice in Traditional Chinese medicine (TCM) rooted in the principle of "medicine and food homology", offers pote...

Predictive, preventive, and personalized medicine in statin-treated patients with NSTE-ACS, HFpEF, and type 2 diabetes: a data-driven model for long-term residual risk assessment.

BACKGROUND: Despite significant advances in guideline-directed medical therapy (GDMT), statin-treated patients with non-ST-elevation acute coronary sy...

Improving Dietary Data Quality in Nutrition Studies: Development and Validation of an Explainable, Reproducible, Open Machine Learning-Assisted Framework for Outlier Detection in 24-Hour Recalls.

Twenty-four-hour dietary recalls (24HRs) are widely used in nutritional epidemiology, but repeated administration is required to capture within-person...

Osteosarcopenia Revisited: From Mechanisms to Management.

Sarcopenia and osteoporosis are characterized by insufficient mass and function of skeletal muscle and bone, and often co-occur in older persons, a co...

Training Perspectives from the NIH T32 Artificial Intelligence for Precision Nutrition Programs.

Nutrition is one of the few modifiable risk factors for health status. The diet-disease relationship, however, is highly complex, with many endogenous...

High dietary B12 is associated with reduced gut microbial B12 biosynthesis capacity and lower fecal short-chain fatty acids in healthy United States adults.

Vitamin B12 is acquired through the consumption of animal-source foods and supplements. In animal models, interventions with B12 and/or methionine inf...

Composite dietary antioxidant index with hepatic indices for predicting mortality in cardiovascular-kidney-metabolic syndrome: Integrated analysis of a nationwide cohort study using machine learning approaches.

Oxidative stress is a pathological driver of cardiovascular-kidney-metabolic (CKM) syndrome, exacerbating inflammation and tissue injury, while metabo...