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Electrocardiogram signal classificat...

Moein, Sara, (1983-)

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Electrocardiogram signal classification and machine learning = emerging research and opportunities /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Electrocardiogram signal classification and machine learning/ by Sara Moein.
Reminder of title:	emerging research and opportunities /
Author:	Moein, Sara,
Published:	Hershey, Pennsylvania :IGI Global, : [2018],
Description:	1 online resource (xiv, 196 p.)
[NT 15003449]:	Chapter 1. Medical diagnosis -- Chapter 2. Introduction to heart -- Chapter 3. Definition of artificial neural network -- Chapter 4. Swarm optimization -- Chapter 5. Feature extraction -- Chapter 6. Literature review -- Chapter 7. Methodology -- Chapter 8. Kinetic gas molecule optimization (KGMO) -- Chapter 9. Classification and feature extraction.
Subject:	Electrocardiography. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5580-3
ISBN:	9781522555810 (ebook)

Electrocardiogram signal classification and machine learning = emerging research and opportunities /
Moein, Sara,1983-

Electrocardiogram signal classification and machine learningemerging research and opportunities /[electronic resource] :by Sara Moein. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xiv, 196 p.)

Includes bibliographical references and index.

Chapter 1. Medical diagnosis -- Chapter 2. Introduction to heart -- Chapter 3. Definition of artificial neural network -- Chapter 4. Swarm optimization -- Chapter 5. Feature extraction -- Chapter 6. Literature review -- Chapter 7. Methodology -- Chapter 8. Kinetic gas molecule optimization (KGMO) -- Chapter 9. Classification and feature extraction.

Restricted to subscribers or individual electronic text purchasers.

"This book develops an intelligent system to classify electrocardiogram signal classification signals for 4 common heart disorders, which are supraventricular tachycardia, bundle branch block, anterior myocardial infarction (Anterior MI), and inferior myocardial infarction (Inferior MI) as well as the normal healthy class"--Provided by publisher.

ISBN: 9781522555810 (ebook)Subjects--Topical Terms:

773588
Electrocardiography.

LC Class. No.: RC683.5.E5 / E44 2018e

Dewey Class. No.: 616.1/207547

National Library of Medicine Call No.: WG 140 / .E44 2018e

Electrocardiogram signal classification and machine learning = emerging research and opportunities /
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020 $a 9781522555810 (ebook)
020 $a 9781522555803 (hardcover)
035 $a (OCoLC)1033673278
035 $a 1071025301
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
050 4 $a RC683.5.E5 $b E44 2018e
060 1 0 $a WG 140 $b .E44 2018e
082 0 4 $a 616.1/207547 $2 23
100 1 $a Moein, Sara, $d 1983- $e author. $3 3310948
245 1 0 $a Electrocardiogram signal classification and machine learning $h [electronic resource] : $b emerging research and opportunities / $c by Sara Moein.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2018]
300 $a 1 online resource (xiv, 196 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Medical diagnosis -- Chapter 2. Introduction to heart -- Chapter 3. Definition of artificial neural network -- Chapter 4. Swarm optimization -- Chapter 5. Feature extraction -- Chapter 6. Literature review -- Chapter 7. Methodology -- Chapter 8. Kinetic gas molecule optimization (KGMO) -- Chapter 9. Classification and feature extraction.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book develops an intelligent system to classify electrocardiogram signal classification signals for 4 common heart disorders, which are supraventricular tachycardia, bundle branch block, anterior myocardial infarction (Anterior MI), and inferior myocardial infarction (Inferior MI) as well as the normal healthy class"--Provided by publisher.
650 0 $a Electrocardiography. $3 773588
650 0 $a Signal processing $x Digital techniques. $3 624853
650 0 $a Machine learning. $3 533906
650 0 $a Heart $x Diseases $x Diagnosis. $3 861315
650 0 $a Pattern recognition systems. $3 527885
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5580-3