Ontology driven knowledge base for high risk pregnancy management
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 im...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2016
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/73439/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963957521&doi=10.1109%2fICICI-BME.2015.7401362&partnerID=40&md5=70c891bdcd6f91c3ead0367be46cd9e4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |
| Summary: | 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. |
|---|