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Ontology Based Recommender System for Diabetic Patients

Received: 29 September 2021    Accepted: 28 October 2021    Published: 17 November 2021
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Abstract

Chronic diseases are a persistent and long-lasting human health conditions that lasts for more than three months. Today the prevalence of chronic non-communicable diseases in Ethiopia increases rapidly because of different reasons like poor nutrition habit, lack of physical activities, drinking alcohols, smoking and life style issues. To overcome this problem different technological applications are developed globally to support both the health professional in diagnosis process and the patients for their self-treatment activities. Ontology helps to create common understanding between human and computers, enable reusability of information, and allows sharing of concepts. Ontology based personalized recommendation model is for diabetic patient in Ethiopian context. We have used design science research methodology in our proposed study. In the development of the proposed model, first we have developed the patient and domain or disease ontology and then the two ontologies needs to integrate in order to develop the required recommendation model. We have used Protégé ontology development tool for the development of the proposed domain or disease and patient ontology. This research discusses how to develop patient and domain or disease ontology and then it also describes how two ontologies need to integrate in order to develop the required recommendation model.

Published in International Journal of Intelligent Information Systems (Volume 10, Issue 6)
DOI 10.11648/j.ijiis.20211006.11
Page(s) 109-116
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Chronic Non-communicable Diseases, Information Retrieval, Ontology, Recommendation Model

References
[1] Alamu. (2014). “Here title of article”, Journal of Multidisciplinary Engineering Science and Technology (JMEST), 1 (3).
[2] Ken et al. (2006). “The Design Science Research Process: A Model for Producing and Presenting Information Systems Research”.
[3] Mukasine A. (2014). “Ontology-Based Personalized System to Support Diabetic Patients at home”.
[4] Solomon et al. (2014). “The prevalence of non-communicable diseases in northwest Ethiopia: survey of Dabat Health and Demographic Surveillance System”.
[5] Thirugnanam et al. (2013). "An Ontology Based System for Predicting Disease using SWRL Rules". International Journal of Computer Science and Business Informatics, 7.
[6] Tian. (2014). “An Ontology-Based Decision Support System for Interventions based on Monitoring Medical Conditions on Patients in Hospital Wards”.
[7] Vandana. (2007). “Ontology for Information system design methodology”.
[8] John H Gennari et al. (2003). “The evolution of Protégé: an environment for knowledge-based systems development”.
[9] WHO. (2011). “Non-communicable diseases country profiles.”
[10] Yohannes et al. (2013). “The impact of dietary risk factors on the burden of non-communicable disease in Ethiopia.
[11] Marut et al. (2016). An Ontology-based Framework for Development of Clinical Reminder System to” Support Chronic Disease Healthcare.
[12] Mingang et al (2017). Performance Evaluation of Recommender Systems. International journal of performablity Engineering.
[13] Mohammad (2010). Understanding semantic web and ontologies: Theory and applications. Journal of computing, volume 2, 182-192.
Cite This Article
  • APA Style

    Simachew Melaku, Melkamu Beyene. (2021). Ontology Based Recommender System for Diabetic Patients. International Journal of Intelligent Information Systems, 10(6), 109-116. https://doi.org/10.11648/j.ijiis.20211006.11

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    ACS Style

    Simachew Melaku; Melkamu Beyene. Ontology Based Recommender System for Diabetic Patients. Int. J. Intell. Inf. Syst. 2021, 10(6), 109-116. doi: 10.11648/j.ijiis.20211006.11

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    AMA Style

    Simachew Melaku, Melkamu Beyene. Ontology Based Recommender System for Diabetic Patients. Int J Intell Inf Syst. 2021;10(6):109-116. doi: 10.11648/j.ijiis.20211006.11

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  • @article{10.11648/j.ijiis.20211006.11,
      author = {Simachew Melaku and Melkamu Beyene},
      title = {Ontology Based Recommender System for Diabetic Patients},
      journal = {International Journal of Intelligent Information Systems},
      volume = {10},
      number = {6},
      pages = {109-116},
      doi = {10.11648/j.ijiis.20211006.11},
      url = {https://doi.org/10.11648/j.ijiis.20211006.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20211006.11},
      abstract = {Chronic diseases are a persistent and long-lasting human health conditions that lasts for more than three months. Today the prevalence of chronic non-communicable diseases in Ethiopia increases rapidly because of different reasons like poor nutrition habit, lack of physical activities, drinking alcohols, smoking and life style issues. To overcome this problem different technological applications are developed globally to support both the health professional in diagnosis process and the patients for their self-treatment activities. Ontology helps to create common understanding between human and computers, enable reusability of information, and allows sharing of concepts. Ontology based personalized recommendation model is for diabetic patient in Ethiopian context. We have used design science research methodology in our proposed study. In the development of the proposed model, first we have developed the patient and domain or disease ontology and then the two ontologies needs to integrate in order to develop the required recommendation model. We have used Protégé ontology development tool for the development of the proposed domain or disease and patient ontology. This research discusses how to develop patient and domain or disease ontology and then it also describes how two ontologies need to integrate in order to develop the required recommendation model.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Ontology Based Recommender System for Diabetic Patients
    AU  - Simachew Melaku
    AU  - Melkamu Beyene
    Y1  - 2021/11/17
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ijiis.20211006.11
    DO  - 10.11648/j.ijiis.20211006.11
    T2  - International Journal of Intelligent Information Systems
    JF  - International Journal of Intelligent Information Systems
    JO  - International Journal of Intelligent Information Systems
    SP  - 109
    EP  - 116
    PB  - Science Publishing Group
    SN  - 2328-7683
    UR  - https://doi.org/10.11648/j.ijiis.20211006.11
    AB  - Chronic diseases are a persistent and long-lasting human health conditions that lasts for more than three months. Today the prevalence of chronic non-communicable diseases in Ethiopia increases rapidly because of different reasons like poor nutrition habit, lack of physical activities, drinking alcohols, smoking and life style issues. To overcome this problem different technological applications are developed globally to support both the health professional in diagnosis process and the patients for their self-treatment activities. Ontology helps to create common understanding between human and computers, enable reusability of information, and allows sharing of concepts. Ontology based personalized recommendation model is for diabetic patient in Ethiopian context. We have used design science research methodology in our proposed study. In the development of the proposed model, first we have developed the patient and domain or disease ontology and then the two ontologies needs to integrate in order to develop the required recommendation model. We have used Protégé ontology development tool for the development of the proposed domain or disease and patient ontology. This research discusses how to develop patient and domain or disease ontology and then it also describes how two ontologies need to integrate in order to develop the required recommendation model.
    VL  - 10
    IS  - 6
    ER  - 

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Author Information
  • Department of Information Technology, Faculty of Technology, Debre Tabor University, Debre Tabor, Ethiopia

  • Information Retrieval, School of Information Science, Addis Ababa University, Addis Ababa, Ethiopia

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