BibTeX:

@article{IJIRSTV1I9064,
     title={Implementation of Data Mining Algorithm to Analysis Breast Cancer},
     author={K.Shiny, M.Swaminathan, N.Siva Kumar and L.Thiyagarajan},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={9},
     pages={207--212},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I9064.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

The aim is to evaluate the analytical data to see if the domain can be a subject to data mining. The next step is to evaluate several data mining methods with respect to their applicability to the given data. This is to show which of the techniques are particularly usable for the given dataset. Finally, the research aims at extracting some tangible medical knowledge from the set. The research utilizes a data warehouse to store the data. The data is accessed via the ETL process. The performance of the data mining models is measured with the use of the lift charts and confusion (classification) matrices. The medical knowledge is extracted based on the indications of the majority of the models. The experiments are conducted in the Microsoft SQL Server 2005.The data mining models were not unanimous about patterns in the data. Thus the medical knowledge is not certain and requires verification from the medical people. However, most of the models strongly associated patient's age, tissue type, hormonal therapies and disease in family with the malignancy of cancers. The next step of the research is to present the findings to the medical people for verification. In the future the outcomes may constitute a good background for development of a Medical Decision Support System.

Medical data mining, Medical data warehouse, medical data, breast cancer