Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{143690,
        author = {Anu Bura and DR. Prakash Kumar Pathak},
        title = {Data Mining tools and techniques in Medical Science},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {1},
        pages = {149-158},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143690},
        abstract = {Our research is based on the Study of various data mining techniques and tools that are used and in Medical Science. In this study we have conclude the techniques , breast cancer and Chronic and kidney Disease. The major goal of the classification technique is to predict the target class accurately for each case in the data. The present study is focused on the usage of classification techniques in the field of medical science and bioinformatics.The goal of data mining application is to turn that data are facts, numbers, or text which can be processed by a computer into knowledge or information. The main purpose of data mining application in healthcare systems is to develop an automated tool for identifying and disseminating relevant healthcare information.Breast cancer is one of the leading cancers for women in developed countries including India. It is the second most common cause of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last years.Chronic- Kidney-Disease prediction using weka data mining tool and its usage for classification in the field of medical bioinformatics. It firstly classifies dataset and then determines which algorithm performs better for diagnosis and prediction of Chronic- Kidney-Disease. Prediction begins with identification of symptoms in patients and then identifying sick patients from a lot of sick and healthy ones. presents a comparative study of different data mining applications, techniques and different methodologies applied for extracting knowledge from database generated in the healthcare industry. Finally, the existing data mining techniques with data mining algorithms and its application tools which are more valuable for healthcare services are discussed in detail.},
        keywords = {},
        month = {},
        }