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506 Finite element modelling of cardiac ischemia and data mining application for ischemic detection and localization
Smiljana Đorović 1 , Marko Robnik-Šikonja 2 , Milos Radović 1 , Bojana Anđelković Ćirković 1 , Nenad Filipović 1

1  Faculty of Engineering, University of Kragujevac, 34000 Kragujevac, Serbia
2  Faculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia

Published: 24 May 2018 by MDPI AG in Proceedings of The Eighteenth International Conference of Experimental Mechanics in The Eighteenth International Conference of Experimental Mechanics
MDPI AG, Volume 2; 10.3390/ICEM18-05269

The main aim of this paper was to computationally simulate the cardiac ischemia employing Finite Element Method (FEM) and detect its presence and localization using data mining approach. A simplified heart-torso model was created based on computed tomography (CT) images, with performed segmentation of the heart (17 zones). Ischemic and non-ischemic cardiac beats were simulated in different zones with aim to create a virtual database which was used for data mining. Using the virtual database, we trained several classifiers and tested them for the purpose of ischemic beat detection based on the body surface potentials map (BSPM). If the ECG is classified as ischemic by the first stage classifier, potentials were processed by the second stage data mining model, which predicted the location of the ischemic area. The use of the second stage classifier, which located the ischemia in one of the heart’s segments created in the FEM model, goes beyond the current state of the art. Thus, the proposed approach is improved solution which can instantly allow clinicians to implement an adequate treatment strategy in future.

Keywords: Data mining, Finite element modeling, cardiac ischemia

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