Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2012.030108
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 3 Issue 1, 2012.
Abstract: In today’s world, healthcare is the most important factor affecting human life. Due to heavy work load it is not possible for personal healthcare. The proposed system acts as a preventive measure for determining whether a person is fit or unfit based on his/her historical and real time data by applying clustering algorithms viz. K-means and D-stream. Both clustering algorithms are applied on patient’s biomedical historical database. To check the correctness of both the algorithms, we apply them on patient’s current biomedical data. The Density-based clustering algorithm i.e. the D-stream algorithm overcomes drawbacks of K-means algorithm. By calculating their performance measures we finally find out effectiveness and efficiency of both the algorithms.
Dipti Patil, Bhagyashree Agrawal, Snehal Andhalkar, Richa Biyani, Mayuri Gund and Dr. V.M.Wadhai, “An Adaptive parameter free data mining approach for healthcare application” International Journal of Advanced Computer Science and Applications(IJACSA), 3(1), 2012. http://dx.doi.org/10.14569/IJACSA.2012.030108