Diet & Nutrition

Artificial Intelligence in Type 1 Diabetes Management: A Scoping Review of Randomised Controlled Trials.

BACKGROUND: Artificial intelligence is emerging in healthcare systems. In type 1 diabetes, AI-enabled tools are increasingly used to support nutrition assessment and insulin decision-making, yet their clinical utility and safety remain unclear. METHODS: The study aims to identify and map the evidence on the clinical utility of AI-based diabetes management tools in people with type 1 diabetes. We c...

The relationship between sarcopenia and all-cause and cardiovascular mortality risk among middle-aged and older adults across stages 0-3 of cardiovascular-kidney-metabolic syndrome: evidence from NHANES and CHARLS.

BACKGROUND: Sarcopenia has been proved to be associated with cardiovascular diseases, chronic kidney disease, and metabolic disorders, but the relationship between sarcopenia and all-cause and cardiovascular mortality risk among middle-aged and older adults across stages 0-3 of cardiovascular-kidney-metabolic (CKM) syndrome remains unclear. PURPOSE: To investigate the relationship between sarcopen...

Molecular-level insights into the role of dissolved black carbon in promoting anaerobic biodegradation of pharmaceuticals in sediments.

The role of dissolved black carbon (DBC) as an extracellular electron transfer carrier in pharmaceutical biodegradation mechanisms, along with its red...

Associations between 12 insulin resistance surrogates with metabolic dysfunction-associated steatotic liver disease risk and all-cause mortality: data from the NHANES III (1988-1994).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) has been shown to be intimately linked to the presence of insulin resista...

Thymic health consequences in adults.

The thymus is essential for establishing T cell diversity early in life, but undergoes profound involution with age and has therefore traditionally be...

Advances and opportunities in measuring dietary intake: from omics to AI.

Accurate measurement of dietary intake remains a cornerstone challenge in optimizing the efficacy of nutritional interventions in human disease. Tradi...

Association of accelerated biological aging with obstructive sleep apnea symptoms and identification of a candidate biomarker gene signature.

BACKGROUND: Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that is linked to cardiovascular, metabolic, and neurocognitive...

Deep Learning Echocardiographic Trajectories of Heart Failure With Preserved Ejection Fraction: A Retrospective Cohort Study.

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a dynamic chronic disease. Specific disease trajectories remain unclear. OBJECTI...

Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time.

BACKGROUND: Timely recognition of oral anticoagulant use is critical in acute stroke but is often hampered by impaired consciousness and unavailable m...

Discovering anti-obesity blue food compounds via combined deep learning and in silico approaches.

Limited validity of an AI-powered app for dietary assessment in females with obesity.

Artificial intelligence (AI) is transforming dietary assessment, yet few tools have been clinically validated against physiological reference methods....

Enabling recycling of critical metals for electric vehicles.

The transition to net-zero emissions is driving electric vehicle (EV) deployment, with global EV stock expected to surpass 350 million by 2030, rising...

Joint effects of physical activity and diet quality on depressive symptoms and all-cause mortality in adults with diabetes: NHANES 2007-2018.

Depressive symptoms are common among adults with diabetes and are associated with adverse clinical outcomes, including mortality. Evidence from genera...

A metabolomics-driven machine learning model for osteoporosis risk prediction.

Osteoporosis, marked by decreased bone mineral density (BMD), poses a major public health concern by increasing fracture risk, lowering quality of lif...

Longitudinal prediction of BMI using explainable AI: integrating polygenic scores, maternal, early-life and familial factors.

BACKGROUND/OBJECTIVES: This study aimed to predict body mass index (BMI) trajectories from childhood to early adulthood using explainable artificial i...

Exploring approaches to computational representation and classification of user-generated meal logs.

OBJECTIVE: This study examined the use of machine learning (ML) and domain-specific enrichment in patient-generated health data, in the form of free-t...

Unsupervised identification of muscle phenotypes in adults with obesity: a data-driven framework for the identification of sarcopenia in absence of a gold standard.

BACKGROUND: Sarcopenia is characterized by progressive loss of skeletal muscle mass and strength and is associated with increased disability and morta...

Predictors of weight gain in under-five children with severe acute malnutrition: A machine learning analysis of a tertiary care hospital dataset.

BACKGROUND & AIMS: Nutritionally rehabilitating children admitted to hospitals with severe acute malnutrition (SAM) and acute illness can pose signifi...

Use of artificial intelligence and radiomics for diagnosis and prediction of osteoporotic fractures: a systematic review.

AIM: Osteoporosis (OP) is a prevalent metabolic bone disease causing millions of fractures annually, leading to significant healthcare and economic bu...

Epilepsy: Modern Treatment Approaches, Clinical Aspects, and Patent Status.

Epilepsy is a chronic neurological disorder causing recurrent seizures. Improved diagnosis and management, including high-resolution imaging, genetic ...