Reprint
The Application of Computer Techniques to ECG Interpretation
Edited by
February 2022
212 pages
- ISBN978-3-0365-3141-0 (Hardback)
- ISBN978-3-0365-3140-3 (PDF)
This book is a reprint of the Special Issue The Application of Computer Techniques to ECG Interpretation that was published in
Biology & Life Sciences
Medicine & Pharmacology
Summary
This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
electrocardiographic imaging (ECGI); heart failure (HF); cardiac resynchronization therapy (CRT); ultrasound; strain; speckle tracking echocardiography; in silico; electrophysiology; electrocardiogram; ECG; cardiac disease; arrhythmia; ischemia; standardization; computerized ECG; personalized medicine; telemedicine; digital ECG data interchange protocol; eHealth; ECG equipment; computerized electrocardiograph; ECG analysis algorithms; computerized ECG interpretation; interatrial block; partial interatrial block; advanced interatrial block; atypical patterns; electrocardiogram (ECG); automated ECG analysis; CSE study; age; sex; race; historical aspects; electronic cohort; electrocardiogram; mortality; big data; telehealth; alarm fatigue; annotation of ECG data; arrhythmia alarms; intensive care unit; patient monitoring; ambulatory ECG; machine learning; deep learning; pattern recognition; noise reduction; Holter ECG; electrocardiogram; ECG interpretation; artificial intelligence; machine learning; body surface mapping; electrocardiographic imaging; image processing; clinical applications; n/a