Prevention

Integrating multi-omics data for personalized nutrition using knowledge graphs and graph neural networks: A comprehensive review.

This comprehensive review focuses on the use of knowledge graphs and Graph Neural Networks (GNNs) to integrate multi-omics data in the field of personalized nutrition. It investigates how different biological datasets-like genomics, proteomics, metabolomics, and gut microbiome profiles-can be combined to create customized dietary plans. By reviewing scientific literature from 2015 to 2025, the stu...

Effects of Real-Time Notification of AI-Detected Incidental Coronary Artery Calcium on Statin Prescription: The NOTIFY-PICTURE Trial.

A systematic review of the role of wearable devices and artificial intelligence applications in assessing functional outcomes after lumbar fusion.

BACKGROUND CONTEXT: As the population ages, rates of lumbar spine disease have risen, and lumbar fusion surgeries have become more prevalent. There ha...

GPT-4o in Nutrition for Inpatients Undergoing Post-Stroke Rehabilitation: Identifying Dietary Errors, Exploring Expert-AI Rationale Differences, and Structuring AI-Expert Collaboration.

OBJECTIVE: Inpatients undergoing stroke rehabilitation experience high malnutrition rates, requiring strict dietary management. However, manual and ti...

Age-specific modifiable determinants and nonlinear risk patterns of habitual low back pain in a large medical check-up cohort: a cross-sectional and longitudinal analysis.

BACKGROUND: Age-related mechanisms underlying habitual low-back pain (LBP) remain poorly defined, with most studies pooling heterogeneous populations ...

Precision Nutritional Genomics, Gut Microbiota and Artificial Intelligence in Chronic Kidney Disease.

Chronic kidney disease (CKD) is a prevalent global health issue, and nutritional management of CKD is an integral component through all stages of the ...

Artificial Intelligence-Based Algorithms Improve Care of Patients with AAA.

BACKGROUND: Timely detection and monitoring of abdominal aortic aneurysms (AAAs) are necessary to prevent ruptures and decrease mortality. Artificial ...

Honey bee nutritranscriptomics reveals key insights towards precision nutrition.

INTRODUCTION: Honey bees are essential managed pollinators faced by nutritional deficiencies which contributes to worldwide colony losses. The integra...

Development of an interpretable machine learning model to predict short-term bleeding risk in patients receiving dual antithrombotic therapy following cardiac surgery.

INTRODUCTION: Bleeding is a serious complication in cardiac surgery, especially among patients receiving combined anticoagulant and antiplatelet thera...

Integrating generative AI in perinatology: applications for literature review.

Perinatology relies on continuous engagement with an expanding body of clinical literature, yet the volume and velocity of publications increasingly e...

Intersections of Educational Attainment, Indigenous Identity, and Race/Ethnicity Best Predicted Diet Quality Among Adults in Canada: A Conditional Random Forests Analysis.

BACKGROUND: Although it is well-known that diet quality varies according to multiple dimensions of socioeconomic position (SEP), much remains unknown ...

Lifestyle-associated serum metabolites profiling in relation to risk of late-onset psoriasis.

BACKGROUND: Although healthy lifestyle behaviours are associated with a lower risk of psoriasis, the underlying metabolic mechanisms remain unclear. O...

Technologies for equine welfare and performance monitoring under field conditions - Where do we stand?

The need for comprehensive equine welfare assessments has become particularly evident amid ongoing debates about the social licence to operate in eque...

Using machine learning to predict the consumption of a Mediterranean diet with untargeted metabolomics data from controlled feeding studies.

BACKGROUND AND AIMS: Developing metabolomic signatures of diets is a promising strategy to better understand the diet-health paradigm. Our objective w...

Integrative machine learning approach to risk prediction for dementia and Alzheimer's disease.

Dementia, particularly Alzheimer's disease (AD), presents a growing global health challenge characterized by cognitive decline, behavioral changes, an...

Evaluation of ChatGPT accuracy and reliability in answering questions about exercise recommendations for breast cancer survivors.

OBJECTIVE: To assess the accuracy and reliability of an artificial intelligence (AI) chatbot (ChatGPT) in providing answers about exercise recommendat...

A Scoping Review on AI-Supported Interventions for Non-Pharmacological Management of Chronic Rheumatic Diseases.

This review summarizes AI-supported non-pharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose,...

Inferring concussion history in athletes using pose and ground reaction force estimation and stability analysis of plyometric exercise videos.

Concussions present a significant risk to athletes, with females exhibiting higher rates and prolonged recovery times than males. Current sideline con...

A pilot study of the potential role of ChatGPT in stated-calorie diet planning.

BACKGROUND/OBJECTIVES: Developments in artificial intelligence encourage society to seek advice from artificial intelligence regarding nutrition recom...

Data Acquisition of Exercise and Fitness Pressure Measurement Based on Artificial Intelligence Technology.

This project aims to improve the accuracy of fitness and physical pressure ratings, focusing on basketball, by integrating artificial intelligence (AI...