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Cardiovascular Computing—Methodologies and Clinical Applications

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Cover of 'Cardiovascular Computing—Methodologies and Clinical Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Cardiovascular Anatomy and Physiology: Basic Principles and Challenges
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    Chapter 2 Current and Emerging Technologies for Cardiovascular Imaging
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    Chapter 3 Cardiac Mechanical Signals
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    Chapter 4 Time-Domain Analysis of the Electrocardiogram
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    Chapter 5 Estimation of Cardiovascular Variability
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    Chapter 6 Segmentation of Cardiac Structures
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    Chapter 7 Automated Techniques for Vessel Detection and Segmentation in Cardiovascular Images
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    Chapter 8 Intrinsic Cardiovascular Wave and Strain Imaging
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    Chapter 9 Image-Based Motion and Strain Estimation of the Vessel Wall
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    Chapter 10 Modelling the Electrical Activity of the Heart
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    Chapter 11 Mathematical and Computational Modelling of Blood Pressure and Flow
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    Chapter 12 Artificial Organs
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    Chapter 13 Tele-, Mobile- and Web-Based Technologies in Cardiovascular Medicine
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    Chapter 14 Artificial Intelligence and Data Mining Methods for Cardiovascular Risk Prediction
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    Chapter 15 Title Cardiovascular Big Data Analytics
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    Chapter 16 Ultrasound Asymptomatic Carotid Plaque Image Analysis for the Prediction of the Risk of Stroke
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    Chapter 17 Signal Analysis in Atrial Fibrillation
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    Chapter 18 Cardiovascular Computing in the Intensive Care Unit
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Mentioned by

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1 Wikipedia page

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20 Mendeley
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Title
Cardiovascular Computing—Methodologies and Clinical Applications
Published by
Springer Singapore, September 2018
DOI 10.1007/978-981-10-5092-3
ISBNs
978-9-81-105091-6, 978-9-81-105092-3
Editors

Golemati, Spyretta, Nikita, Konstantina S.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 30%
Student > Ph. D. Student 4 20%
Researcher 3 15%
Other 2 10%
Student > Bachelor 1 5%
Other 0 0%
Unknown 4 20%
Readers by discipline Count As %
Engineering 8 40%
Computer Science 4 20%
Medicine and Dentistry 2 10%
Chemistry 1 5%
Unknown 5 25%