Diet & Nutrition

Low-carbohydrate diet score and chronic obstructive pulmonary disease: a machine learning analysis of NHANES data.

BACKGROUND: Recent research has identified the Low-Carbohydrate Diet (LCD) score as a novel biomarker, with studies showing that LCDs can reduce carbon dioxide retention, potentially improving lung function. While the link between the LCD score and chronic obstructive pulmonary disease (COPD) has been explored, its relevance in the US population remains uncertain. This study aims to explore the as...

Artificial Intelligence and Environmental Impact: Moving Beyond Humanizing Vocabulary and Anthropocentrism.

Artificial intelligence (AI) and its applications in digital health, bioengineering, and society have significant material impacts on the environment owing to AI's vast energy demands and energy consumption, carbon footprints, and water usage to cool data centers and generate electricity to power the data centers. Yet, the environmental footprints of AI remain underappreciated and inadequately ack...

Standardized evaluation of diabetic retinopathy using artificial intelligence and its association with metabolic dysfunction-associated steatotic liver disease in Japan: A cross-sectional study.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications...

Serum Vitamin D Profiles of Children with Asthma in Southwest Saudi: A Comparative Cross-Sectional Study.

BACKGROUND: Evidence suggests a strong association between vitamin D status and asthma, with individuals exhibiting vitamin D deficiency demonstrating...

Cytotoxicity, Antiadipogenic, Low-Density Lipoprotein Oxidation Inhibitory Activities, and Acute Toxicity Study of Hydroethanolic Leaf and Bark Extracts.

Obesity is increasingly taking an important stage as a cause of death worldwide, and interventions with a good cost-effectiveness ratio are needed. ...

Chemical-functional characterization of and and dietary supplementation in post-weaning pigs.

INTRODUCTION: As the livestock industry grapples with the need for sustainable land, maintaining production systems, and reducing antimicrobial resist...

Ovarian reserve modulates the impact of vitamin D deficiency on assisted reproductive outcomes in patients undergoing controlled ovarian hyperstimulation.

OBJECTIVE: The association between vitamin D deficiency and ovarian reserve-specific outcomes of assisted reproductive technology (ART) remains uncert...

Dietary caffeine and its negative link to serum Klotho concentrations: evidence from the National Health and Nutrition Examination Survey.

BACKGROUND: This is the initial investigation assessing the association between caffeine consumption through diet and circulating Klotho concentration...

Enhancing Nitrogen Nutrition Index estimation in rice using multi-leaf SPAD values and machine learning approaches.

Accurate nitrogen diagnosis is essential for optimizing rice yield and sustainability. This study investigates the potential of using multi-leaf SPAD ...

An explainable predictive model for anxiety symptoms risk among Chinese older adults with abdominal obesity using a machine learning and SHapley Additive exPlanations approach.

BACKGROUND: Early detection of anxiety symptoms can support early intervention and may help reduce the burden of disease in later life in the elderly ...

Comprehensive Investigation of Machine Learning and Deep Learning Networks for Identifying Multispecies Tomato Insect Images.

Deep learning applications in agriculture are advancing rapidly, leveraging data-driven learning models to enhance crop yield and nutrition. Tomato ()...

Novel study designs and modelling approaches in nutrition research: application of advanced statistical modelling approaches and N-of-1 study designs.

Randomised controlled trials are the 'gold standard' approach in nutrition research to show a causal relationship between a dietary intervention and c...

Good practices and common pitfalls of machine learning in nutrition research.

Machine learning is increasingly being utilised across various domains of nutrition research due to its ability to analyse complex data, especially as...

AcidAGE: a biological age determination neural network based on urine organic acids.

Organic acids reflect the course of all important metabolic processes and the effects of diet, nutrient deficiency, lifestyle, and microbiota composit...

Milk ladder: Who? When? How? Where? with the lowest risk of reaction.

The milk ladder (ML) approach, which is the gradual reintroduction of the milk allergen from the least allergenic forms to the most allergenic forms i...

Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models.

A significant portion of the world's population relies on rice as a primary source of nutrition. In Malaysia, rice production began in the early 1960s...

Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea.

This study aimed to develop and validate a machine learning (ML)-based model for predicting liposuction volumes in patients with obesity. This study u...

anti-cancer activity of siddha metallo-mineral formulation from Thanga uram with Hela cell lines.

The second most common malignant tumour in women worldwide, cervical cancer seriously jeopardizes their health. It has been established that a high-ri...

Artificial Intelligence Applications to Measure Food and Nutrient Intakes: Scoping Review.

BACKGROUND: Accurate measurement of food and nutrient intake is crucial for nutrition research, dietary surveillance, and disease management, but trad...

The factors affecting aerobics athletes' performance using artificial intelligence neural networks with sports nutrition assistance.

This work aims to comprehensively explore the influencing factors of aerobics athletes' performance by integrating sports nutrition assistance and art...