A hybrid model of Maximum Margin Clustering method and Support Vector Regression for noninvasive electrocardiographic imaging

DOI10.1155/2012/436281zbMath1261.92027OpenAlexW2080514086WikidataQ36413645 ScholiaQ36413645MaRDI QIDQ1929559

Guofa Shou, Huaxiong Zhang, Ya-Ming Wang, Wenqing Huang, Feng Liu, Mingfeng Jiang

Publication date: 9 January 2013

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2012/436281

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biomedical imaging and signal processing (92C55)

Related Items

The combination of self-organizing feature maps and support vector regression for solving the inverse ECG problem

Uses Software

• LIBSVM
• GAToolBox

Cites Work

• On the possibility for computing the transmembrane potential in the heart with a one shot method: an inverse problem
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