Mining a Small Medical Data Set by Integrating the Decision Tree and t-test

[[abstract]]Although several researchers have used statistical methods to prove that aspiration followed by the injection of 95% ethanol left in situ (retention) is an effective treatment for ovarian endometriomas, very few discuss the different conditions that could generate different recovery rates for the patients. Therefore, this study adopts the statistical method and decision tree techniques together to analyze the postoperative status of ovarian endometriosis patients under different conditions. Since our collected data set is small, containing only 212 records, we use all of these data as the training data. Therefore, instead of using a resultant tree to generate rules directly, we use the value of each node as a cut point to generate all possible rules from the tree first. Then, using t-test, we verify the rules to discover some useful description rules after all possible rules from the tree have been generated. Experimental results show that our approach can find some new interesting knowledge about recurrent ovarian endometriomas under different conditions.[[journaltype]]國外[[incitationindex]]EI[[booktype]]紙本[[countrycodes]]FI

A Unified Data Grid Replication Framework

Modern scientific experiments can generate large amounts of data, which may be replicated and distributed across multiple resources to improve application performance and fault tolerance. Whilst a number of different replica management systems exist, particular communities usually adopt a single system. This creates problems when an application program spans more than one community, because it may need to target more than one middleware layer. One solution to this problem is to build a more flexible data access layer above the specific replica middleware. In this paper, we discuss such an architecture, the Grid Replication Framework, which provides applications with an abstract interface to existing replica systems. Further, the framework’s flexible plug-in architecture makes it easy to support new middleware as it becomes available. 1