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Diet

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AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review.

Annals of medicine
OBJECTIVE: Human error estimating food intake is a major source of bias in nutrition research. Artificial intelligence (AI) methods may reduce bias, but the overall accuracy of AI estimates is unknown. This study was a systematic review of peer-revie...

Principles and Validations of an Artificial Intelligence-Based Recommender System Suggesting Acceptable Food Changes.

The Journal of nutrition
BACKGROUND: Along with the popularity of smartphones, artificial intelligence-based personalized suggestions can be seen as promising ways to change eating habits toward more desirable diets.

Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight.

Journal of medical systems
Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in...

Tracing human life trajectory using gut microbial communities by context-aware deep learning.

Briefings in bioinformatics
The gut microbial communities are highly plastic throughout life, and the human gut microbial communities show spatial-temporal dynamic patterns at different life stages. However, the underlying association between gut microbial communities and time-...

Machine learning-based colorectal cancer prediction using global dietary data.

BMC cancer
BACKGROUND: Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Active health screening for CRC yielded detection of an increasingly younger adults. However, current machine learning algorithms that are trained using older ...

Alternative additives associated in the feeding of laying hens: performance, biometrics, bone traits, and economic evaluation-an unsupervised machine learning approach.

Tropical animal health and production
Given the current bans on the use of some growth promoting antibiotics in poultry nutrition, the need to use alternative additives which could replace traditional promoters in diets has arisen. The objective of this study was to evaluate the effect o...

Predicting Unreported Micronutrients From Food Labels: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Micronutrient deficiencies represent a major global health issue, with over 2 billion individuals experiencing deficiencies in essential vitamins and minerals. Food labels provide consumers with information regarding the nutritional conte...

The Role of Artificial Intelligence in Deciphering Diet-Disease Relationships: Case Studies.

Annual review of nutrition
Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to an increased prevalence of cardiometabolic and additional noncommunicable diseases, such as cancer, i...

Virtual Screening of Nrf2 Dietary-Derived Agonists and Safety by a New Deep-Learning Model and Verified and .

Journal of agricultural and food chemistry
Nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is an essential regulatory target of antioxidants, but the lack of Nrf2 active site information has hindered discovery of new Nrf2 agonists from food-derived compounds by large-scale virtual screenin...

Surveying Nutrient Assessment with Photographs of Meals (SNAPMe): A Benchmark Dataset of Food Photos for Dietary Assessment.

Nutrients
Photo-based dietary assessment is becoming more feasible as artificial intelligence methods improve. However, advancement of these methods for dietary assessment in research settings has been hindered by the lack of an appropriate dataset against whi...