Abstract
The distributed case-based reasoning consists of distributing the reasoning through a set of agents and the cases through a set of case bases for improving the performance and for ensuring the maintainability of the reasoning system. The most important challenge of the medical applications resides in the precision of decisions; hence the novel decision support systems should introduce more aspects of reasoning for achieving this criterion. In this paper, we describe a cognitive amalgam with a distributed case-based reasoning enriched by an expert system which infer from an XML knowledge base extracted from the domain expertise. Each cognitive agent capitalises its knowledge from same class cases by using a machine learning algorithm enriched by a fuzzy similarity measures function. The aim of this proposition is to reach the optimal criteria of medical applications. The achieved experimental results applied in the diagnosis of complex type of data obtained from the electrocardiogram ECG signal improves our proposition and promotes more realisations in the medical domain.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Information and Communication Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
