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NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment

Nutrients, 2017-06, Vol.9 (7), p.657

2017

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A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations

PloS one, 2017-06, Vol.12 (6), p.e0179488-e0179488

2017

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A Fine-Tuned Bidirectional Encoder Representations From Transformers Model for Food Named-Entity Recognition: Algorithm Development and Validation

Journal of medical Internet research, 2021-08, Vol.23 (8), p.e28229

2021

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Dietary Intakes of Slovenian Adults and Elderly: Design and Results of the National Dietary Study SI.Menu 2017/18

Nutrients, 2022-09, Vol.14 (17), p.3618

2022

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ISO-FOOD ontology: A formal representation of the knowledge within the domain of isotopes for food science

Food chemistry, 2019-03, Vol.277, p.382-390

2019

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StandFood: Standardization of Foods Using a Semi-Automatic System for Classifying and Describing Foods According to FoodEx2

Nutrients, 2017-05, Vol.9 (6), p.542

2017

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Water Wins, Communication Matters: School-Based Intervention to Reduce Intake of Sugar-Sweetened Beverages and Increase Intake of Water

Nutrients, 2022-03, Vol.14 (7), p.1346

2022

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Deep Neural Networks for Image-Based Dietary Assessment

Journal of visualized experiments, 2021-03 (169)

2021

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Workflow for building interoperable food and nutrition security (FNS) data platforms

Trends in food science & technology, 2022-05, Vol.123, p.310-321

2022

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Vitamin D Intake in Slovenian Adolescents, Adults, and the Elderly Population

Nutrients, 2021-10, Vol.13 (10), p.3528

2021

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Optimising an FFQ Using a Machine Learning Pipeline to teach an Efficient Nutrient Intake Predictive Model

Nutrients, 2020-12, Vol.12 (12), p.3789

2020

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Dietary Intake of Adolescents and Alignment with Recommendations for Healthy and Sustainable Diets: Results of the SI.Menu Study

Nutrients, 2024-06, Vol.16 (12), p.1912

2024

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SnackTrack-An App-Based Tool to Assess the Influence of Digital and Physical Environments on Snack Choice

Nutrients, 2023-01, Vol.15 (2), p.349

2023

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A multi-center survey on hospital malnutrition and cachexia in Slovenia

European journal of clinical nutrition, 2020-03, Vol.74 (3), p.419-426

2020

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From language models to large-scale food and biomedical knowledge graphs

Scientific reports, 2023-05, Vol.13 (1), p.7815-7815, Article 7815

2023

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Dietary Intake and Status of Vitamin B12 in Slovenian Population

Nutrients, 2022-01, Vol.14 (2), p.334

2022

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Dietary Iron Intake and Biomarkers of Iron Status in Slovenian Population: Results of SI.Menu/Nutrihealth Study

Nutrients, 2022-12, Vol.14 (23), p.5144

2022

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Total and Free Sugars Consumption in a Slovenian Population Representative Sample

Nutrients, 2020-06, Vol.12 (6), p.1729

2020

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P-NUT: Predicting NUTrient Content from Short Text Descriptions

Mathematics (Basel), 2020-10, Vol.8 (10), p.1811

2020

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Domain Heuristic Fusion of Multi-Word Embeddings for Nutrient Value Prediction

Mathematics (Basel), 2021-08, Vol.9 (16), p.1941

2021

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COVID-19 pandemic changes the food consumption patterns

Trends in food science & technology, 2020-10, Vol.104, p.268-272

2020

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Data-Driven Preference-Based Deep Statistical Ranking for Comparing Multi-objective Optimization Algorithms

Bioinspired Optimization Methods and Their Applications, 2018, Vol.10835, p.138-150

2018

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MIGHT: Statistical Methodology for Missing-Data Imputation in Food Composition Databases

Applied sciences, 2019-10, Vol.9 (19), p.4111

2019

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The Slovenian food composition database

Food chemistry, 2013-10, Vol.140 (3), p.495-499

2013

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Inadequate Intake of Dietary Fibre in Adolescents, Adults, and Elderlies: Results of Slovenian Representative SI. Menu Study

Nutrients, 2021-10, Vol.13 (11), p.3826

2021

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NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment

A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations

A Fine-Tuned Bidirectional Encoder Representations From Transformers Model for Food Named-Entity Recognition: Algorithm Development and Validation

Dietary Intakes of Slovenian Adults and Elderly: Design and Results of the National Dietary Study SI.Menu 2017/18

ISO-FOOD ontology: A formal representation of the knowledge within the domain of isotopes for food science

StandFood: Standardization of Foods Using a Semi-Automatic System for Classifying and Describing Foods According to FoodEx2

Water Wins, Communication Matters: School-Based Intervention to Reduce Intake of Sugar-Sweetened Beverages and Increase Intake of Water

Deep Neural Networks for Image-Based Dietary Assessment

Workflow for building interoperable food and nutrition security (FNS) data platforms

Vitamin D Intake in Slovenian Adolescents, Adults, and the Elderly Population

Optimising an FFQ Using a Machine Learning Pipeline to teach an Efficient Nutrient Intake Predictive Model

Dietary Intake of Adolescents and Alignment with Recommendations for Healthy and Sustainable Diets: Results of the SI.Menu Study

SnackTrack-An App-Based Tool to Assess the Influence of Digital and Physical Environments on Snack Choice

A multi-center survey on hospital malnutrition and cachexia in Slovenia

From language models to large-scale food and biomedical knowledge graphs

Dietary Intake and Status of Vitamin B12 in Slovenian Population

Dietary Iron Intake and Biomarkers of Iron Status in Slovenian Population: Results of SI.Menu/Nutrihealth Study

Total and Free Sugars Consumption in a Slovenian Population Representative Sample

P-NUT: Predicting NUTrient Content from Short Text Descriptions

Domain Heuristic Fusion of Multi-Word Embeddings for Nutrient Value Prediction

COVID-19 pandemic changes the food consumption patterns

Data-Driven Preference-Based Deep Statistical Ranking for Comparing Multi-objective Optimization Algorithms

MIGHT: Statistical Methodology for Missing-Data Imputation in Food Composition Databases

The Slovenian food composition database

Inadequate Intake of Dietary Fibre in Adolescents, Adults, and Elderlies: Results of Slovenian Representative SI. Menu Study

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