Title :
Fuzzy Partition Rules for Heart Arrhythmia Detection
Author :
Omar Behadada;Marcello Trovati
Author_Institution :
Dept. of Biomed. Eng., Fac. of Technol., Algeria
Abstract :
In this paper, we discuss a method to define semi-automatically fuzzy partition rules to provide a powerful and accurate insight into cardiac arrhythmia. As suggested by our evaluation, this provide a robust, scalable, and accurate system, which can successfully tackle the challenges posed by the utilization of big data in the medical sector.
Keywords :
"Accuracy","Decision trees","Electrocardiography","Data mining","Pragmatics","Medical diagnostic imaging","Fuzzy logic"
Conference_Titel :
Intelligent Networking and Collaborative Systems (INCOS), 2015 International Conference on
DOI :
10.1109/INCoS.2015.50
