Journal article
Detection of delayed gastric emptying from electrogastrograms with support vector machine
IEEE transactions on biomedical engineering, v 48(5), pp 601-604
May 2001
PMID: 11341535
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A recent study reported a conventional neural network (NN) approach for the noninvasive diagnosis of delayed gastric emptying from the cutaneous electrogastrograms. Using support vector machine, we show that this relatively new technique can be used for detection of delayed gastric emptying and is in fact able to outdo the conventional NN.
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Details
- Title
- Detection of delayed gastric emptying from electrogastrograms with support vector machine
- Creators
- H Liang - Center for Complex Systems, Florida Atlantic University, Boca Raton 33431, USA. liang@walt.ccs.fau.eduZ Lin
- Publication Details
- IEEE transactions on biomedical engineering, v 48(5), pp 601-604
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE); United States
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000168315200012
- Scopus ID
- 2-s2.0-0035034374
- Other Identifier
- 991014878222704721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical