Classification of electrocardiogram and auscultatory blood pressure signals using machine learning models
In this paper, two real-world medical classification problems using electrocardiogram (ECG) and auscultatory blood pressure (Korotkoff) signals are examined. A total of nine machine learning models are applied to perform classification of the medical data sets. A number of useful performance metrics...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
2015
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Subjects: | |
Online Access: | http://eprints.um.edu.my/13942/1/Classification_of_electrocardiogram_and_auscultatory_blood_pressure.pdf http://eprints.um.edu.my/13942/ http://ac.els-cdn.com/S095741741400801X/1-s2.0-S095741741400801X-main.pdf?_tid=bacd29d8-e7cf-11e4-a4fa-00000aab0f6c&acdnat=1429584190_a9c034bfc0490d7fb60fc36edb602f9c |
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Institution: | Universiti Malaya |
Language: | English |
Internet
http://eprints.um.edu.my/13942/1/Classification_of_electrocardiogram_and_auscultatory_blood_pressure.pdfhttp://eprints.um.edu.my/13942/
http://ac.els-cdn.com/S095741741400801X/1-s2.0-S095741741400801X-main.pdf?_tid=bacd29d8-e7cf-11e4-a4fa-00000aab0f6c&acdnat=1429584190_a9c034bfc0490d7fb60fc36edb602f9c