An Efficient K-Means Clustering Algorithm Using Euclidean Distance Techniques

Abstract: The quality of the healthcare and treatment outcome relies heavily on Data Mining field to exchange information for accurate detection of the life threatening causes. The quality of health care system can be improved by employing an intelligent system via the Data Mining Techniques. Data Mining Techniques are used to reveal the hidden patterns from the vast collection of patient�s data. Analysis of the data uses techniques and statistical measures to get insight into vast patient�s information and predict the possible causes for the health issues and its impact on individual patients. Earlier analysis of the health related issues will reduce psychological stress and gives enormous time to identify the specialist in the respective field to acquire pre-determined treatment.

Keywords: Data Mining, Agglomerative, Clustering, K-Means, K-Medoids, Dataset in Excel.