Development of knowledge-based ontology framework for diabetes patients in medical applications
Conference: BIBE 2018 - International Conference on Biological Information and Biomedical Engineering
06/06/2018 - 06/08/2018 at Shanghai, China
Proceedings: BIBE 2018
Pages: 4Language: englishTyp: PDF
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Authors:
Chen, Li (School of Software, Nanchang University, Nanchang, 330047, Jiangxi, China & Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China)
Lu, Dongxin (Shenzhen Youle life Health Management Co. Ltd, 518055, Shenzhen, China)
Pirbhulal, Sandeep; Chen, Zhenda; Wu, Hongyan (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China)
Sodhro, Ali Hassan (DISP LAB, University Lumiere Lyon 2, Lyon, France)
Huang, Guixin (The First Affiliated Hospital, Sun Yat-sen University, 510080, Guangzhou, China)
Abstract:
Diabetes is a disease that affects an estimated 422 million adults, and the total costs of diagnosed diabetes have raised more than $245 billion. The main limitations of existing, ontology-based methods for diagnosing diabetes are that they not only have semantic inconsistencies, but also they have not provided a complete, clinical approach due to consideration of a few numbers of classes in their models. In this study, a knowledge-based ontology framework (KBOF) is developed for screening and treating diabetic patients. The proposed KBOF provides a complete semantic and clinical approach by adding more detailed analysis of patients based on a standard ontology. We have implemented the developed KBOF on Web Ontology Language (OWL), which is a semantic-web language; it enables us to create a knowledge-based representation of diabetic patients by applying different parameters. From the comparative analysis, we observed that the proposed KBOF is more feasible and accurate than traditional models for managing diabetes.