AIMC Topic: Food

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LeFood-set: Baseline performance of predicting level of leftovers food dataset in a hospital using MT learning.

PloS one
Monitoring the remaining food in patients' trays is a routine activity in healthcare facilities as it provides valuable insights into the patients' dietary intake. However, estimating food leftovers through visual observation is time-consuming and bi...

Food Recommendation as Language Processing (F-RLP): A Personalized and Contextual Paradigm.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
State-of-the-art rule-based and classification-based food recommendation systems face significant challenges in becoming practical and useful. This difficulty arises primarily because most machine learning models struggle with problems characterized ...

A snail species identification method based on deep learning in food safety.

Mathematical biosciences and engineering : MBE
In daily life, snail classification is an important mean to ensure food safety and prevent the occurrence of situations that toxic snails are mistakenly consumed. However, the current methods for snail classification are mostly based on manual labor,...

Tracking of Nutritional Intake Using Artificial Intelligence.

Studies in health technology and informatics
In this short communication paper, we present the results we achieved for automated calorie intake measurement for patients with obesity or eating disorders. We demonstrate feasibility of applying deep learning based image analysis to a single pictur...

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...

Mediterranean Food Image Recognition Using Deep Convolutional Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We present a new dataset of food images that can be used to evaluate food recognition systems and dietary assessment systems. The Mediterranean Greek food -MedGRFood dataset consists of food images from the Mediterranean cuisine, and mainly from the ...

Food for thought: A natural language processing analysis of the 2020 Dietary Guidelines publice comments.

The American journal of clinical nutrition
BACKGROUND: The Administrative Procedure Act of 1946 guarantees the public an opportunity to view and comment on the 2020 Dietary Guidelines as part of the policymaking process. In the past, public comments were submitted by postal mail or public hea...

Machine Learning Uncovers Food- and Excipient-Drug Interactions.

Cell reports
Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ing...

FOBI: an ontology to represent food intake data and associate it with metabolomic data.

Database : the journal of biological databases and curation
Nutrition research can be conducted by using two complementary approaches: (i) traditional self-reporting methods or (ii) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these t...

FoodBase corpus: a new resource of annotated food entities.

Database : the journal of biological databases and curation
The existence of annotated text corpora is essential for the development of public health services and tools based on natural language processing (NLP) and text mining. Recently organized biomedical NLP shared tasks have provided annotated corpora re...