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Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities

Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities

Copyright: © 2018 |Pages: 196
ISBN13: 9781522555803|ISBN10: 1522555803|EISBN13: 9781522555810
DOI: 10.4018/978-1-5225-5580-3
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MLA

Moein, Sara. Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities. IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5580-3

APA

Moein, S. (2018). Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities. IGI Global. https://doi.org/10.4018/978-1-5225-5580-3

Chicago

Moein, Sara. Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5580-3

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Technological tools and computational techniques have enhanced the healthcare industry. These advancements have led to significant progress in the diagnosis of heart disorders.

Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities is a critical scholarly resource that examines the importance of automatic normalization and classification of electrocardiogram (ECG) signals of heart disorders. Featuring a wide range of topics such as common heart disorders, particle swarm optimization, and benchmarks functions, this publication is geared toward medical professionals, researchers, professionals, and students seeking current and relevant research on the categorization of ECG signals.

Table of Contents

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Front Materials
Title Page
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Copyright Page
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Advances in Medical Technologies and Clinical Practice (AMTCP) Book Series
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Dedication
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Preface
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Acknowledgment
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Chapters
Back Materials
Conclusion
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Compilation of References
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About the Author
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Index
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