Universiti Teknologi Malaysia Institutional Repository

Ontology driven knowledge base for high risk pregnancy management

Lam, J. and Noor, Y. A. and Supriyanto, E. (2016) Ontology driven knowledge base for high risk pregnancy management. In: 4th International Conference on Instrumentation, Communications, Information Technology and Biomedical Engineering, ICICI-BME 2015, 2-3 Nov 2015, Bandung, Indonesia.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

High risk pregnancy can lead both mother and developing fetus to death. Proper antenatal care before and during pregnancy may decrease the risk of complications. Clinical decision support system (CDSS) is one of health information systems for assisting health providers in decision making that can improve the quality of prenatal care. However, there are difficulties in CDSS's knowledge maintenance. Ontology, in the other hand is well known for its flexibility. In this study, Ontology driven knowledge base for high risk pregnancy is developed and evaluated. Seven criterias are included in this ontology, including risk factors, health issues, findings, pregnancy status, preventive measures, management, and health promotion. 25 participants evaluated the system by using six criterias: understandibility, completeness, correctness, flexibility, simplicity, and integrity. The result implies that the system developed is good, but not satisfying enough. The knowledge given is adequate for midwives. Maintaning knowledge and ensuring the system's scalability will be the future challenge for this study.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:decision support system, health informatics, high risk pregnancy, knowledge base, ontology
Subjects:Q Science > QH Natural history
Divisions:Biosciences and Medical Engineering
ID Code:73439
Deposited By: Mohd Zulaihi Zainudin
Deposited On:23 Nov 2017 09:37
Last Modified:23 Nov 2017 09:37

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