A Knowledge-Based Data Mining System for Diagnosing Malaria Related Cases in Healthcare Management
A Knowledge-Based Data Mining System for Diagnosing Malaria Related Cases in Healthcare Management
Olugbenga Oluwagbemi 1, Uzoamaka Ofoezie2 , Nwinyi,Obinna 3
1Rochester Institute of Technology, 28 Lomb Memorial Drive, Rochester NY 14623, Rochester , New York, USA 2 (Bioinformatics Unit) Departments of Computer and Information Sciences
School of Natural and Applied Sciences College of Science and Technology, Covenant University, Ogun State, Nigeria.
3Department of Biological sciences, School of Natural and Applied Sciences
College of Science and Technology, Covenant University, Ogun State, Nigeria.
gbemiseun@yahoo.com
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.
Keywords: diagnosis, data mining, malaria
1. Introduction
Data mining as a process for analyzing data from different perspectives and summarizing it into useful information can generate information that can be used to increase revenue, cut costs, or both [1]. Data mining identifies trends within data that go beyond simple analysis. Through the
Olugbenga Oluwagbemi 1, Uzoamaka Ofoezie2 , Nwinyi,Obinna 3
1Rochester Institute of Technology, 28 Lomb Memorial Drive, Rochester NY 14623, Rochester , New York, USA 2 (Bioinformatics Unit) Departments of Computer and Information Sciences
School of Natural and Applied Sciences College of Science and Technology, Covenant University, Ogun State, Nigeria.
3Department of Biological sciences, School of Natural and Applied Sciences
College of Science and Technology, Covenant University, Ogun State, Nigeria.
gbemiseun@yahoo.com
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.
Keywords: diagnosis, data mining, malaria
1. Introduction
Data mining as a process for analyzing data from different perspectives and summarizing it into useful information can generate information that can be used to increase revenue, cut costs, or both [1]. Data mining identifies trends within data that go beyond simple analysis. Through the
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