Oluwagbemi, O. O. and Ofoezie, Uzoamaka and Nwinyi, Obinna (2010) A Knowledge-Based Data Mining System for Diagnosing Malaria Related Cases in Healthcare Management. Egyptian Computer Science Journal, 34 (4).
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Abstract
Data mining a process for assembling and analyzing data into useful information can be applied as rapid measures for malaria diagnosis. In this research work we implemented (knowledge-base) inference engine that will help in mining sample patient records to discover interesting relationships in malaria related cases. The computer programming language employed was the C#.NET programming language and Microsoft SQL Server 2005 served as the Relational Database Management System (RDBMS). The results obtained showed that knowledge-based data mining system was able to successfully mine out and diagnose possible diseases corresponding to the selected symptoms entered as query. With this finding, we believe the development of a Knowledge-based data mining system will not only be beneficial towards the diagnosis of malaria related cases in a more cost effective means but will assist in crucial decision making and new policy formulation in the malaria endemic regions.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Mr Adewole Adewumi |
| Date Deposited: | 07 Feb 2011 11:53 |
| Last Modified: | 13 Dec 2011 21:13 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/46 |
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