A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis
The World Health Organization (WHO) indicates that the proportion of the elderly will soon include nearly a quarter of the world population. Ensuring that health systems are prepared to deal with this phenomenal rate of aging and associated diseases generates many challenges. Among these challenges...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9311736/ |
| _version_ | 1818921800340340736 |
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| author | Nora Shoaip Amira Rezk Shaker El-Sappagh Louai Alarabi Sherif Barakat Mohammed M. Elmogy |
| author_facet | Nora Shoaip Amira Rezk Shaker El-Sappagh Louai Alarabi Sherif Barakat Mohammed M. Elmogy |
| author_sort | Nora Shoaip |
| collection | DOAJ |
| description | The World Health Organization (WHO) indicates that the proportion of the elderly will soon include nearly a quarter of the world population. Ensuring that health systems are prepared to deal with this phenomenal rate of aging and associated diseases generates many challenges. Among these challenges is facing Alzheimer's Disease (AD) that may occur at some point in the elderly life and may harm societies. AD is considered a neurological, psychological, mental, and health setback. The Clinical Decision Support System (CDSS) can improve patient care and support many medical functions, such as diagnosing diseases that can reduce preventable harm. This research's main objective is to design, implement, and evaluate the Alzheimer's Disease Diagnosis Ontology (ADDO). It is a comprehensive semantic knowledge base toward the development of fuzzy ontology-based CDSS for AD diagnosis. ADDO can serve as a core component of CDSS, which provides representation, annotation, and access to aspects related to AD's study and diagnosis. Toward the management of this objective, ADDO is based on the essentials of the Open Biomedical Ontology (OBO) and follows the Basic Formal Ontology (BFO) and the Ontology for General Medical Sciences (OGMS) principles. ADDO focuses on representing the patient characteristics, complications, drugs, diagnosis examination tests, and key aspects of their periodic visits in a standard way. The possibility of semantic interoperability is taken into account by integrating ADDO and a heterogeneous AD dataset. We used ADNI as a case study to mapping a set of real instances. To manage the medical domain's uncertainty, ADDO is extended to fuzzy ontology to accommodate the medical linguistic variables and enhance diagnosis results' efficiency. ADDO is constructed using Protégé 5.5.0 software and evaluated using the HermiT reasoner and SPARQL semantic queries. ADDO currently includes 7060 concepts, 99 properties, 46274 axioms, and 30708 annotations. As a result, ADDO is consistent and more reliable in managing most AD aspects than other existing AD ontologies. |
| first_indexed | 2024-12-20T01:43:24Z |
| format | Article |
| id | doaj.art-10e323bbca6a43f5ac5b1bee8b854bee |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T01:43:24Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-10e323bbca6a43f5ac5b1bee8b854bee2022-12-21T19:57:49ZengIEEEIEEE Access2169-35362021-01-019313503137210.1109/ACCESS.2020.30484359311736A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease DiagnosisNora Shoaip0https://orcid.org/0000-0001-6767-4163Amira Rezk1https://orcid.org/0000-0002-7646-4915Shaker El-Sappagh2Louai Alarabi3https://orcid.org/0000-0001-7746-3618Sherif Barakat4Mohammed M. Elmogy5https://orcid.org/0000-0002-2504-6051Department of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura, EgyptDepartment of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura, EgyptCentro Singular de Investigación en Tecnoloxías Intelixentes (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, SpainDepartment of Computer Science, Umm Al-Qura University, Makkah, Saudi ArabiaDepartment of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura, EgyptDepartment of Information Technology, Faculty of Computers and Information, Mansoura University, Mansoura, EgyptThe World Health Organization (WHO) indicates that the proportion of the elderly will soon include nearly a quarter of the world population. Ensuring that health systems are prepared to deal with this phenomenal rate of aging and associated diseases generates many challenges. Among these challenges is facing Alzheimer's Disease (AD) that may occur at some point in the elderly life and may harm societies. AD is considered a neurological, psychological, mental, and health setback. The Clinical Decision Support System (CDSS) can improve patient care and support many medical functions, such as diagnosing diseases that can reduce preventable harm. This research's main objective is to design, implement, and evaluate the Alzheimer's Disease Diagnosis Ontology (ADDO). It is a comprehensive semantic knowledge base toward the development of fuzzy ontology-based CDSS for AD diagnosis. ADDO can serve as a core component of CDSS, which provides representation, annotation, and access to aspects related to AD's study and diagnosis. Toward the management of this objective, ADDO is based on the essentials of the Open Biomedical Ontology (OBO) and follows the Basic Formal Ontology (BFO) and the Ontology for General Medical Sciences (OGMS) principles. ADDO focuses on representing the patient characteristics, complications, drugs, diagnosis examination tests, and key aspects of their periodic visits in a standard way. The possibility of semantic interoperability is taken into account by integrating ADDO and a heterogeneous AD dataset. We used ADNI as a case study to mapping a set of real instances. To manage the medical domain's uncertainty, ADDO is extended to fuzzy ontology to accommodate the medical linguistic variables and enhance diagnosis results' efficiency. ADDO is constructed using Protégé 5.5.0 software and evaluated using the HermiT reasoner and SPARQL semantic queries. ADDO currently includes 7060 concepts, 99 properties, 46274 axioms, and 30708 annotations. As a result, ADDO is consistent and more reliable in managing most AD aspects than other existing AD ontologies.https://ieeexplore.ieee.org/document/9311736/Fuzzy ontologyclinical decision support systemAlzheimer’s diseaseknowledge basedMild COGNITIVE impairmentontology representation |
| spellingShingle | Nora Shoaip Amira Rezk Shaker El-Sappagh Louai Alarabi Sherif Barakat Mohammed M. Elmogy A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis IEEE Access Fuzzy ontology clinical decision support system Alzheimer’s disease knowledge based Mild COGNITIVE impairment ontology representation |
| title | A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis |
| title_full | A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis |
| title_fullStr | A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis |
| title_full_unstemmed | A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis |
| title_short | A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis |
| title_sort | comprehensive fuzzy ontology based decision support system for alzheimer x2019 s disease diagnosis |
| topic | Fuzzy ontology clinical decision support system Alzheimer’s disease knowledge based Mild COGNITIVE impairment ontology representation |
| url | https://ieeexplore.ieee.org/document/9311736/ |
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