The healthcare industry collects a huge amount of data which is not properly mined and not put to the optimum use. Discovery of these hidden patterns and relationships often goes unexploited. Our research focuses on this aspect of Medical diagnosis by learning pattern through the collected data of hepatitis and to develop intelligent medical decision support systems to help the physicians. In this paper, we propose the use of decision trees C4.5 algorithm, ID3 algorithm and CART algorithm to classify these diseases and compare the effectiveness, correction rate among them. Thus, the CART derived model along with the extended definition for identifying (diagnosing) hepatitis disease provided a good classification accuracy based model.
No takes yet. Share an insight, caveat, or question.
G. Sathyadevi (2011) studied this question.
Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context: