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ML-Based Cardiac Arrhythmia Diagnosis using ECG and PPG Signal Features - by Lakshmi Devi R (Paperback)
$28.49 sale price when purchased online
$32.99 list price
Target Online store #3991
About this item
Highlights
- "ML-Based Cardiac Arrhythmia Diagnosis using ECG and PPG Signal Features" by Lakshmi Devi R. is an innovative and comprehensive study on the use of machine learning algorithms for the diagnosis of cardiac arrhythmia using electrocardiogram (ECG) and photoplethysmogram (PPG) signal features.Through detailed research and analysis, Lakshmi Devi R. highlights the potential benefits of machine learning in accurately detecting various types of cardiac arrhythmias.
- Author(s): Lakshmi Devi R
- 184 Pages
- Technology, Biomedical
Description
Book Synopsis
"ML-Based Cardiac Arrhythmia Diagnosis using ECG and PPG Signal Features" by Lakshmi Devi R. is an innovative and comprehensive study on the use of machine learning algorithms for the diagnosis of cardiac arrhythmia using electrocardiogram (ECG) and photoplethysmogram (PPG) signal features.Through detailed research and analysis, Lakshmi Devi R. highlights the potential benefits of machine learning in accurately detecting various types of cardiac arrhythmias. The author also discusses the significance of using both ECG and PPG signals to improve the accuracy of the diagnosis.
Whether you are a healthcare professional looking for new approaches to diagnosing cardiac arrhythmias or a researcher interested in the latest advancements in the field, "ML-Based Cardiac Arrhythmia Diagnosis using ECG and PPG Signal Features" is an essential resource.
Order your copy today and discover how machine learning can play a vital role in improving the accuracy and efficiency of cardiac arrhythmia diagnosis.
Dimensions (Overall): 9.0 Inches (H) x 6.0 Inches (W) x .39 Inches (D)
Weight: .56 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 184
Genre: Technology
Sub-Genre: Biomedical
Publisher: Independent Author
Format: Paperback
Author: Lakshmi Devi R
Language: English
Street Date: April 3, 2023
TCIN: 1002216062
UPC: 9786801031627
Item Number (DPCI): 247-32-0488
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 0.39 inches length x 6 inches width x 9 inches height
Estimated ship weight: 0.56 pounds
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