Proximity Measures in Clustering on Patient Diagnosis System

摘要

This work focused on grouping patterns of patient information. Patient symptoms, test results and their ailments are considered to determine the adoption patterns of partitioned groups using clustering approach of data mining. From the analysis, two different groups of patients are analyzed. The patients of similar diseases are grouped as first one. The second group is dissimilar with previous one. This paper utilizes proximity measures are analyzed in cluster of each categories to lead accurate strategic model to improve further treatment of each individual groups.