Development of a Prototype for Critical Disease Predictions using Data Mining

The goal of this paper is to present breast cancer prototype model along with the prediction of heart diseases by employing data mining techniques. The data used in the study had been retrieved from Public-Use Data, which is available online. The data comprised of 699 and 909 records for breast cancer and heart disease respectively. For data prediction and mining, C4.5 and C5.0, which are decision tree algorithms, were used on the data, used in the study. The results of both data sets using both algorithms were also compared. The paper also outlines the significance of evidence based medicine, which is the novel and innovative approach in healthcare decision making process [5]. It is essential that the clinical decisions are supported and based on scientific evidence, which ensures that they are sound and effective decisions. This paper also will depict the importance of data mining in modern healthcare

Discussing the Role of Classification Algorithms in Clinical Predictions with help of Case Studies

This paper discuss about the important role of classification algorithms in clinical predictions , two case studies one for breast cancer and other for heart disease prediction with help of classification data mining techniques is presented in this paper. Online freely accessible data is used for the said case studies. Used data is publicly available data on internet consisting of 909 records for heart disease and 699 for breast cancer. C4.5 and the C5.0 Two well-known decision tree algorithms used to get the rules for predictions, and these rules used for improving the quality of an open source Pathology Management System based on Care2x.Performances of these algorithms are also compared. This Paper will further discuss about the importance of open source software in healthcare as well as how a pathology management system can adopt Evidence Based Medicine (EBM). EBM is a new and important approach which can greatly improve decision making in health care. EBM's task is to prevent, diagnose and medicate diseases using medical evidence [5].Clinical decisions must be based on scientific evidence that demonstrates effectiveness. This paper is basically extension of our previous work ‘A Prototype of Cancer/Heart Disease Prediction Model Using Data Mining’

Development of a Web-enabled Spatial Decision Support System (SDSS) for Prevention of Tick Borne Disease in Kuantan, Malaysia

Ticks are the second most common vectors of human disease after mosquitoes. They are found on many small mammal hosts and also blood-feed on humans with the risk of transmitting diseases. Considering the diseases’ risks, this study has investigated the potential for a web-enabled spatial decision support system (SDSS) to assist government decision-makers in the control, management of resources and prevention of tick borne diseases specifically in the study area of Kuantan, Malaysia