OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems
Millions of adults have diabetes across the globe and the overall cost for managing diabetic patients has reached up to approximately 250 million. A major constraint in existing ontology-based systems for diagnosing and treating diabetes is the presence of semantic inconsistencies and lack of a comp...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-05-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147719847112 |
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| _version_ | 1850209510106333184 |
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| author | Li Chen Dongxin Lu Menghao Zhu Muhammad Muzammal Oluwarotimi Williams Samuel Guixin Huang Weinan Li Hongyan Wu |
| author_facet | Li Chen Dongxin Lu Menghao Zhu Muhammad Muzammal Oluwarotimi Williams Samuel Guixin Huang Weinan Li Hongyan Wu |
| author_sort | Li Chen |
| collection | DOAJ |
| description | Millions of adults have diabetes across the globe and the overall cost for managing diabetic patients has reached up to approximately 250 million. A major constraint in existing ontology-based systems for diagnosing and treating diabetes is the presence of semantic inconsistencies and lack of a comprehensive clinical approach primarily due to consideration of a limited number of classes in the model. In this research, we are focused on building an ontology-based model for diabetic patients by collecting detailed diabetic knowledge of subjects for further diagnosis and treatment. The concept of semantic resources to electronic health record standards is an essential factor for semantic interoperability in remote health monitoring. This study applies semantic web ontology language for developing ontology-based model for diabetic patients to aid doctors in reaching an efficient diagnostic decision about the status of diabetes by applying Semantic Web Rule Language. A total of 766 medical records from clinical environment were selected in this study, and 269 of them were known for developing diabetes. The experimental results suggest that the proposed solution is more accurate in managing diabetes compared to other medical applications. The performance analysis of the ontology-based model for diabetic patients regarding the accuracy of disease prediction, diagnosing diabetes, and recommending medicine is 95%, 98%, and 85%, respectively. |
| format | Article |
| id | doaj-art-983247e85bc0499ebe625d9b961da449 |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2019-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-983247e85bc0499ebe625d9b961da4492025-08-20T02:09:59ZengWileyInternational Journal of Distributed Sensor Networks1550-14772019-05-011510.1177/1550147719847112OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systemsLi Chen0Dongxin Lu1Menghao Zhu2Muhammad Muzammal3Oluwarotimi Williams Samuel4Guixin Huang5Weinan Li6Hongyan Wu7Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaShenzhen Youle Life Health Management Co. Ltd., Shenzhen, ChinaSchool of Software, Beihang University, Beijing, ChinaShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaThe First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaSino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, ChinaShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaMillions of adults have diabetes across the globe and the overall cost for managing diabetic patients has reached up to approximately 250 million. A major constraint in existing ontology-based systems for diagnosing and treating diabetes is the presence of semantic inconsistencies and lack of a comprehensive clinical approach primarily due to consideration of a limited number of classes in the model. In this research, we are focused on building an ontology-based model for diabetic patients by collecting detailed diabetic knowledge of subjects for further diagnosis and treatment. The concept of semantic resources to electronic health record standards is an essential factor for semantic interoperability in remote health monitoring. This study applies semantic web ontology language for developing ontology-based model for diabetic patients to aid doctors in reaching an efficient diagnostic decision about the status of diabetes by applying Semantic Web Rule Language. A total of 766 medical records from clinical environment were selected in this study, and 269 of them were known for developing diabetes. The experimental results suggest that the proposed solution is more accurate in managing diabetes compared to other medical applications. The performance analysis of the ontology-based model for diabetic patients regarding the accuracy of disease prediction, diagnosing diabetes, and recommending medicine is 95%, 98%, and 85%, respectively.https://doi.org/10.1177/1550147719847112 |
| spellingShingle | Li Chen Dongxin Lu Menghao Zhu Muhammad Muzammal Oluwarotimi Williams Samuel Guixin Huang Weinan Li Hongyan Wu OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems International Journal of Distributed Sensor Networks |
| title | OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems |
| title_full | OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems |
| title_fullStr | OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems |
| title_full_unstemmed | OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems |
| title_short | OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems |
| title_sort | omdp an ontology based model for diagnosis and treatment of diabetes patients in remote healthcare systems |
| url | https://doi.org/10.1177/1550147719847112 |
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