State Space Advanced Fuzzy Cognitive Map approach for automatic and non
Invasive diagnosis of Coronary Artery Disease
- URL: http://arxiv.org/abs/2004.03372v2
- Date: Fri, 30 Oct 2020 13:18:04 GMT
- Title: State Space Advanced Fuzzy Cognitive Map approach for automatic and non
Invasive diagnosis of Coronary Artery Disease
- Authors: Ioannis D. Apostolopoulos, Peter P. Groumpos, Dimitris I.
Apostolopoulos
- Abstract summary: Recently emerged advances in Fuzzy Cognitive Maps (FCM) are investigated and employed, for achieving the automatic and non-invasive diagnosis of Coronary Artery Disease (CAD)
A Computer-Aided Diagnostic model for the acceptable and non-invasive prediction of CAD is proposed.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Purpose: In this study, the recently emerged advances in Fuzzy Cognitive Maps
(FCM) are investigated and employed, for achieving the automatic and
non-invasive diagnosis of Coronary Artery Disease (CAD). Methods: A
Computer-Aided Diagnostic model for the acceptable and non-invasive prediction
of CAD using the State Space Advanced FCM (AFCM) approach is proposed. Also, a
rule-based mechanism is incorporated, to further increase the knowledge of the
system and the interpretability of the decision mechanism. The proposed method
is tested utilizing a CAD dataset from the Laboratory of Nuclear Medicine of
the University of Patras. More specifically, two architectures of AFCMs are
designed, and different parameter testing is performed. Furthermore, the
proposed AFCMs, which are based on the new equations proposed recently, are
compared with the traditional FCM approach. Results: The experiments highlight
the effectiveness of the AFCM approach and the new equations over the
traditional approach, which obtained an accuracy of 78.21%, achieving an
increase of seven percent (+7%) on the classification task, and obtaining
85.47% accuracy. Conclusions: It is demonstrated that the AFCM approach in
developing Fuzzy Cognitive Maps outperforms the conventional approach, while it
constitutes a reliable method for the diagnosis of Coronary Artery Disease.
Conclusions and future research related to recent pandemic of coronavirus are
provided.
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