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Food

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Thought on Food: A Systematic Review of Current Approaches and Challenges for Food Intake Detection.

Sensors (Basel, Switzerland)
Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise, other people with dementia, Alzheimer's disease, or other...

Food traceability 4.0 as part of the fourth industrial revolution: key enabling technologies.

Critical reviews in food science and nutrition
Food Traceability 4.0 (FT 4.0) is about tracing foods in the era of the fourth industrial revolution (Industry 4.0) with techniques and technologies reflecting this new revolution. Interest in food traceability has gained momentum in response to, amo...

Tableware Tidying-Up Robot System for Self-Service Restaurant-Detection and Manipulation of Leftover Food and Tableware.

Sensors (Basel, Switzerland)
In this study, an automated tableware tidying-up robot system was developed to tidy up tableware in a self-service restaurant with a large amount of tableware. This study focused on sorting and collecting tableware placed on trays detected by an RGB-...

Exploring the role of green and Industry 4.0 technologies in achieving sustainable development goals in food sectors.

Food research international (Ottawa, Ont.)
In recent years, the rapid increase in the global population, the challenges associated with climate change, and the emergence of new pandemics have all become major threats to food security worldwide. Consequently, innovative solutions are urgently ...

A TastePeptides-Meta system including an umami/bitter classification model Umami_YYDS, a TastePeptidesDB database and an open-source package Auto_Taste_ML.

Food chemistry
Taste peptides with umami/bitterness play a role in food attributes. However, the taste mechanisms of peptides are not fully understood, and the identification of these peptides is time-consuming. Here, we created a taste peptide database by collecti...

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.

Natural language processing and machine learning approaches for food categorization and nutrition quality prediction compared with traditional methods.

The American journal of clinical nutrition
BACKGROUND: Food categorization and nutrient profiling are labor intensive, time consuming, and costly tasks, given the number of products and labels in large food composition databases and the dynamic food supply.

A robust and resilience machine learning for forecasting agri-food production.

Scientific reports
This research proposes a new framework for agri-food capacity production by considering resiliency and robustness and paying attention to disruption and risk for the first time. It is applied robust stochastic optimization by adding robustness to the...

Applying Image-Based Food-Recognition Systems on Dietary Assessment: A Systematic Review.

Advances in nutrition (Bethesda, Md.)
Dietary assessment can be crucial for the overall well-being of humans and, at least in some instances, for the prevention and management of chronic, life-threatening diseases. Recall and manual record-keeping methods for food-intake monitoring are a...

Tongue crack recognition using segmentation based deep learning.

Scientific reports
Tongue cracks refer to fissures with different depth and shapes on the tongue's surface, which can characterize the pathological characteristics of spleen and stomach. Tongue cracks are of great significance to the objective study of tongue diagnosis...