ANALYSIS AND CLASSIFICATION OF ALGORITHMS FOR BREAST-CANCER & DISEASES PREDICTION USING THE DATA MINING WEKA TOOL

Abstract

In the 21st century medical & healthcare facilities are at their disposal vast amounts of breast cancer patients’ data. The identical analysis of available data can be used to facilitate more patients and will lead the decision-making efficiency. During the study it was found that extraction of relevant knowledge from this data and act upon it in a timely manner is challengeable. To troubleshoot this problem and turn into knowledge, use of efficient computing and data mining tools has been suggested. The classification and analysis of this data can aid in developing expert systems for decision support in breast cancer and other diseases. Also this can reduce the cost, the waiting time, and be uses as troubleshooting tools to liberate medical practitioners for more research and reduce errors and mistakes. A research work has been conducted in SRBC Bhopal and analytical data has been used for classification of algorithms for breast Cancer \disease prediction using the data mining Weka Tool. Effective data mining tools can assist in early detection of diseases such as breast cancer.