Gastro-intestinal tract inspired computational model for myocardial infarction diagnosis
Myocardial infarction (MI) has been the major cause of mortality in humans. The diagnostic process of MI in humans is critical and requires careful examination of the general symptoms, heart activity rate and blood chemistry apart from considering the patient history and contextual information of the diagnostic process. The manual diagnostic process often results in high misclassification rate due to the higher level of complexity involved therein. Thus, computer-based diagnostic systems have been developed to assist the medical practitioners for accurately diagnosing MI. However, most of the computer-based techniques are unable to handle and incorporate contextual information associated with the diagnostic process effectively. This paper aims at enhancing the computer aided diagnostic performance and solving the problem of handling contextual information through the development of a novel nature-inspired computational model. The model presented in this paper is based on the defense mechanism associated with the Human Digestive System. It incorporates multi-level decision making approach and the reasoning behind diagnostic indications at different levels of diagnostic process. The proposed diagnostic system, implemented using MATIAB, has been tested on real medical data set. The experimental results of the proposed model have been compared with five standard AI-based classification techniques. The results obtained suggest that the new classification approach presented in this paper is better than the standard AI-based classification solutions in most cases. (C) 2010 Elsevier Ltd. All rights reserved.
myocardial infarction human digestive system artificial intelligence