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Scientific Reports
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April 21, 2022
In-depth insights into Alzheimer's disease by using explainable machine learning approach
Bojan Bogdanovic, Tome Eftimov, Monika Simjanoska
Expert Systems with Applications
|
August 10, 2022
Dietary, comorbidity, and geo-economic data fusion for explainable COVID-19 mortality prediction
Milena Trajanoska, Risto Trajanov, Tome Eftimov
Frontiers in Nutrition
|
September 18, 2024
Zero-shot evaluation of ChatGPT for food named-entity recognition and linking
Matevž Ogrinc, Barbara Koroušić Seljak, Tome Eftimov
Database : the Journal of Biological Databases and Curation
|
November 5, 2019
FoodBase corpus: a new resource of annotated food entities
Gorjan Popovski, Barbara Koroušić Seljak, Tome Eftimov
Plos One
|
June 24, 2017
A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations
Tome Eftimov, Barbara Koroušić Seljak, Peter Korošec
Food and Chemical Toxicology : an International Journal Published for the British Industrial Biological Research Association
|
May 8, 2020
Evaluating missing value imputation methods for food composition databases
Gordana Ispirova, Tome Eftimov, Barbara Koroušić Seljak
Artificial Intelligence in Medicine
|
June 14, 2023
FooDis: A food-disease relation mining pipeline
Gjorgjina Cenikj, Tome Eftimov, Barbara Koroušić Seljak
Nutrients
|
June 8, 2017
StandFood: Standardization of Foods Using a Semi-Automatic System for Classifying and Describing Foods According to FoodEx2
Tome Eftimov, Peter Korošec, Barbara Koroušić Seljak
Frontiers in Nutrition
|
April 10, 2024
NutriGreen image dataset: a collection of annotated nutrition, organic, and vegan food products
Jan Drole, Igor Pravst, Tome Eftimov, et al.
Public Health Nutrition
|
April 7, 2018
Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment
Simon Mezgec, Tome Eftimov, Tamara Bucher, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 29) with videos related to
Sort By:
Page
of 3
Scientific Reports
|
April 21, 2022
In-depth insights into Alzheimer's disease by using explainable machine learning approach
Bojan Bogdanovic, Tome Eftimov, Monika Simjanoska
Expert Systems with Applications
|
August 10, 2022
Dietary, comorbidity, and geo-economic data fusion for explainable COVID-19 mortality prediction
Milena Trajanoska, Risto Trajanov, Tome Eftimov
Frontiers in Nutrition
|
September 18, 2024
Zero-shot evaluation of ChatGPT for food named-entity recognition and linking
Matevž Ogrinc, Barbara Koroušić Seljak, Tome Eftimov
Database : the Journal of Biological Databases and Curation
|
November 5, 2019
FoodBase corpus: a new resource of annotated food entities
Gorjan Popovski, Barbara Koroušić Seljak, Tome Eftimov
Plos One
|
June 24, 2017
A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations
Tome Eftimov, Barbara Koroušić Seljak, Peter Korošec
Food and Chemical Toxicology : an International Journal Published for the British Industrial Biological Research Association
|
May 8, 2020
Evaluating missing value imputation methods for food composition databases
Gordana Ispirova, Tome Eftimov, Barbara Koroušić Seljak
Artificial Intelligence in Medicine
|
June 14, 2023
FooDis: A food-disease relation mining pipeline
Gjorgjina Cenikj, Tome Eftimov, Barbara Koroušić Seljak
Nutrients
|
June 8, 2017
StandFood: Standardization of Foods Using a Semi-Automatic System for Classifying and Describing Foods According to FoodEx2
Tome Eftimov, Peter Korošec, Barbara Koroušić Seljak
Frontiers in Nutrition
|
April 10, 2024
NutriGreen image dataset: a collection of annotated nutrition, organic, and vegan food products
Jan Drole, Igor Pravst, Tome Eftimov, et al.
Public Health Nutrition
|
April 7, 2018
Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment
Simon Mezgec, Tome Eftimov, Tamara Bucher, et al.
Page
of 3