A fast approach for detection of erythemato-squamous diseases based on extreme learning machine with maximum relevance minimum redundancy feature selection

DOI10.1080/00207721.2013.801096zbMath1362.92033DBLPjournals/ijsysc/LiuHMWC15OpenAlexW2017522944WikidataQ62727331 ScholiaQ62727331MaRDI QIDQ5252884

Hui ling Chen, Tong Liu, Zhi-Yan Wang, Chao Ma, Liang Hu

Publication date: 3 June 2015

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2013.801096

zbMATH Keywords

medical diagnosisfeature selectionextreme learning machineMRMRerythemato-squamous diseases diagnosis

Mathematics Subject Classification ID

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

Cites Work

• Implementation of automated diagnostic systems: ophthalmic arterial disorders detection case
• Classification of Parkinson's disease using feature weighting method on the basis of fuzzy C-means clustering

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