research-article

Expert system for nutrition care process of older adults

Authors:

Dianne Reidlinger,

Florin PopAuthors Info & Claims

Future Generation Computer Systems, Volume 80, Issue C

Pages 368 - 383

https://doi.org/10.1016/j.future.2017.05.037

Published: 01 March 2018 Publication History

Abstract

This paper presents an expert system for a nutrition care process tailored for the specific needs of elders. Dietary knowledge is defined by nutritionists and encoded as Nutrition Care Process Ontology, and then used as underlining base and standardized model for the nutrition care planning. An inference engine is developed on top of the ontology, providing semantic reasoning infrastructure and mechanisms for evaluating the rules defined for assessing short and long term elders self-feeding behaviours, to identify unhealthy dietary patterns and detect the early instauration of malnutrition. Our expert system provides personalized intervention plans covering nutrition education, diet prescription and food ordering adapted to the older adults specific nutritional needs, health conditions and food preferences. In-lab evaluation results are presented proving the usefulness and quality of the expert system as well as the computational efficiency, coupling and cohesion of the defined ontology. Expert system for a nutrition care process tailored for the specific needs of elders.An inference engine developed on top of the Nutrition Care Process Ontology.Semantic reasoning for evaluating the self-feeding behaviours rules.Define and semantically represent information.Performance evaluation.

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Cited By

Nahar KBanikhalaf MIbrahim FAbual-Rub MAlmomani AGupta B(2023)A Rule-Based Expert Advisory System for Restaurants Using Machine Learning and Knowledge-Based Systems TechniquesInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.33306419:1(1-25)Online publication date: 7-Nov-2023
https://dl.acm.org/doi/10.4018/IJSWIS.333064
Magnini MCiatto GCantürk FAydoğan ROmicini A(2023)Symbolic knowledge extraction for explainable nutritional recommendersComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2023.107536235:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.cmpb.2023.107536
Ivaşcu TDiniş ACincar K(2018)A Disease-driven Nutrition Recommender System based on a Multi-agent ArchitectureProceedings of the 8th International Conference on Web Intelligence, Mining and Semantics10.1145/3227609.3227685(1-5)Online publication date: 25-Jun-2018
https://dl.acm.org/doi/10.1145/3227609.3227685

Expert system for nutrition care process of older adults
1. Applied computing
  1. Life and medical sciences

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cover image Future Generation Computer Systems

Future Generation Computer Systems Volume 80, Issue C

March 2018

655 pages

ISSN:0167-739X

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Copyright © Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 March 2018

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Cited By

Nahar KBanikhalaf MIbrahim FAbual-Rub MAlmomani AGupta B(2023)A Rule-Based Expert Advisory System for Restaurants Using Machine Learning and Knowledge-Based Systems TechniquesInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.33306419:1(1-25)Online publication date: 7-Nov-2023
https://dl.acm.org/doi/10.4018/IJSWIS.333064
Magnini MCiatto GCantürk FAydoğan ROmicini A(2023)Symbolic knowledge extraction for explainable nutritional recommendersComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2023.107536235:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.cmpb.2023.107536
Ivaşcu TDiniş ACincar K(2018)A Disease-driven Nutrition Recommender System based on a Multi-agent ArchitectureProceedings of the 8th International Conference on Web Intelligence, Mining and Semantics10.1145/3227609.3227685(1-5)Online publication date: 25-Jun-2018
https://dl.acm.org/doi/10.1145/3227609.3227685

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