AIMC Topic: Diet

Clear Filters Showing 1 to 10 of 164 articles

Using AI Chatbot to Assist Students' Behavior Management for Obesity Prevention in Middle Schools: Feasibility Study.

JMIR formative research
BACKGROUND: Adolescent obesity remains a pressing public health challenge, particularly among socioeconomically disadvantaged populations. Artificial intelligence (AI) holds the promise for supporting students in managing daily health behaviors, but ...

Machine learning for screening laryngopharyngeal reflux symptoms in college students: a cross-sectional study.

Annals of medicine
BCKGROUND: Laryngopharyngeal reflux (LPR) is a widespread global health issue. Its recurring symptoms and impact on quality of life create significant economic burdens for individuals and society. To examine the links between lifestyle, diet, and LPR...

Faecal metabolites as a readout of habitual diet capture dietary interactions with the gut microbiome.

Nature communications
The interplay between diet and gut microbiome composition is complex. Faecal metabolites, the end products of human and microbial metabolism, provide insights into these interactions. Here, we integrate faecal metabolomics, metagenomics, and habitual...

Association of the dietary index for gut microbiota with metabolic syndrome and its components combining interpretable machine learning algorithms.

Journal of health, population, and nutrition
BACKGROUND: Previous studies have emphasized the critical role of diet and gut microbiome in Metabolic syndrome (MetS). The dietary index for gut microbiota (DI-GM) represents a novel dietary index that effectively reflects the diversity of gut micro...

Interpretable machine learning for cardiovascular risk prediction: Insights from NHANES dietary and health data.

PloS one
BACKGROUND: Cardiovascular diseases (CVD) are one of the leading global causes of death, which requires an accurate early prediction. This study aimed to develop transparent machine learning (ML) models using National Health and Nutrition Examination...

DHerbKB for CKD: knowledge base of diet and toxic herbal medicines for clinical support of chronic kidney disease.

Journal of translational medicine
BACKGROUND: Dietary management and nephrotoxic herbal medicine control are essential and sophisticated in chronic kidney disease(CKD) care. Information gap between clinical principles and real-world practice hinders the relevant management. It is nec...

Identifying and predicting dietary patterns in the Dutch population using machine learning.

European journal of nutrition
PURPOSE: Nutritional epidemiological research is shifting its focus from individual nutrients to dietary patterns, which challenges traditional statistical methods. Here, we aim to apply various machine learning algorithms to identify and predict die...

Temporal nutrition analysis associates dietary regularity and quality with gut microbiome diversity: insights from the Food & You digital cohort.

Nature communications
The gut microbiota is profoundly influenced by dietary choices, with emerging evidence linking it to various health outcomes. Here, we investigate diet-microbiota associations using detailed temporal nutrition intake data captured through real-time f...

Metabolomics and nutrient intake reveal metabolite-nutrient interactions in metabolic syndrome: insights from the Korean Genome and Epidemiology Study.

Nutrition journal
BACKGROUND: Despite advances in metabolomics, the complex relationship between metabolites and nutrient intake in metabolic syndrome (MetS) remains poorly understood in the Korean population.

The apportionment of dietary diversity in wildlife.

Proceedings of the National Academy of Sciences of the United States of America
Evaluating species' roles in food webs is critical for advancing ecological theories on competition, coexistence, and biodiversity but is complicated by pronounced dietary variability within species and overlap across species. We combined dietary DNA...