Hybrid Knowledge Based System for Pregnancy Related Disease Diagnosis

Shitaw, Lijalem

dc.contributor.author	Shitaw, Lijalem
dc.date.accessioned	2020-06-04T08:12:58Z
dc.date.available	2020-06-04T08:12:58Z
dc.date.issued	2020-02
dc.identifier.uri	http://hdl.handle.net/123456789/10889
dc.description.abstract	Health problems touch every aspect of human life such as health condition, working environment, family life, social relations, economic and political activities of every endeavor. The major challenge for health service in Ethiopia is shortage of skilled manpower in the health sector, In Ethiopia the number of health professionals and patients demand are unequal. Lacks of enough knowledge among primary health care workers, allocation of insufficient budgets for health sectors and the absence of adequate awareness about pregnancy Related diseases are the other challenges that create obstacles to address the health care services satisfactorily. The factors are the challenges that affect the quality of health care service and reduce the quality of decisions made by physicians. As a result, objective of the study is to explore the applicability of hybrid reasoning approach in the development of knowledge-based decision support system for the pregnancy Related diseases diagnosis. This also improve the quality of decision making, provide effective and efficient services, and improve shortage of domain expert in specific domain area. The designed hybrid knowledge-based system use Jcolibri programming tool integrated with Eclipse and Nearest Neighbor retrieval algorithm. The designed prototype system is evaluated differently including statistical analysis, comparative evaluation, user evaluation, and other evaluation techniques. The experimental study shows a significant improvement while the study used a hybrid approach of RBR and CBR as compared with RBR and CBR individually for designing a knowledge-based decision support system. We achieved an overall recognition accuracy of 88.75% while using a hybrid knowledgebased system. We therefore recommended a further investigation on the different reasoning methods so as to improve the knowledge-based decision making.	en_US
dc.language.iso	en	en_US
dc.subject	Information Technology	en_US
dc.title	Hybrid Knowledge Based System for Pregnancy Related Disease Diagnosis	en_US
dc.type	Thesis	en_US