Multiclass maximum margin clustering via immune evolutionary algorithm for automatic diagnosis of electrocardiogram arrhythmias

DOI10.1016/J.AMC.2013.11.028zbMath1365.92052OpenAlexW1980186244MaRDI QIDQ2396485

Bohui Zhu, Yong-Sheng Ding, Kuang-Rong Hao

Publication date: 8 June 2017

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2013.11.028

zbMATH Keywords

maximum margin clusteringECG arrhythmiasimmune evolutionary algorithmmulticlass clustering

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Biomedical imaging and signal processing (92C55) Medical applications (general) (92C50) Computational methods for problems pertaining to biology (92-08)

Cites Work

• Detection of ECG arrhythmia using a differential expert system approach based on principal component analysis and least square support vector machine
• A patient adaptable ECG beat classifier based on neural networks
• Classification of heart rate data using artificial neural network and fuzzy equivalence relation
• 10.1162/15324430260185628
• The Concave-Convex Procedure

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