Simple understandable analysis of medical data to support the diagnostic process

Abstract

Medical diagnostic is a complex process consisting of many input variables, which the general practitioner (GP) or specialist should take into account before confirm the expected diagnosis. In the case of electronic records, they have an opportunity to support this process within simple understandable results of the correctly applied suitable methods from machine learning or statistics. We used a small sample of patient's data from Croatia for experimental evaluation of this potential. We applied the methods as Welch's t-test, Pearson chi-square independence test, Youden's index, decision trees and simple K-Means. The cooperating medical expert evaluated the obtained results and confirmed the expected potential for daily medical practice.