Data Mining in Blood Platelets Transfusion using Classification Rule
Devchand J. Chaudhari, Mamta Ramteke, Manoj G. Lade · 2012
Data mining provides automatic pattern recognition and attempts to uncover patterns in data that are difficult to detect with traditional statistical methods. Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives, databases and summarizing it into useful form called information -information that can be used to increase revenue, cuts costs, or both. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. The goal of this project will be to develop data mining algorithm for transfusion of blood platelets. This algorithm will be adapted to find conditions under which transfusions were successful and those under which platelet transfusions were unsuccessful. This proposal will be useful for finding cancer patient‟s dataset.