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Artificial Intelligence and Machine Learning for Healthcare

Overview of attention for book
Cover of 'Artificial Intelligence and Machine Learning for Healthcare'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Artificial Intelligence in Healthcare
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    Chapter 2 Radiomics: Approach to Precision Medicine
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    Chapter 3 Artificial Intelligence Based Strategies for Data-Driven Radial MRI
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    Chapter 4 Unsupervised Domain Adaptation Approach for Liver Tumor Detection in Multi-phase CT Images
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    Chapter 5 Multi-stage Synthetic Image Generation for the Semantic Segmentation of Medical Images
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    Chapter 6 Classification of Arrhythmia Signals Using Hybrid Convolutional Neural Network (CNN) Model
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    Chapter 7 Polyp Segmentation with Deep Ensembles and Data Augmentation
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    Chapter 8 Autistic Verbal Behavior Parameters
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    Chapter 9 Advances in Modelling Hospital Medical Wards
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    Chapter 10 Tracking Person-Centred Care Experiences Alongside Other Success Measures in Hearing Rehabilitation
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    Chapter 11 BioGNN: How Graph Neural Networks Can Solve Biological Problems
Attention for Chapter 6: Classification of Arrhythmia Signals Using Hybrid Convolutional Neural Network (CNN) Model
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Readers on

mendeley
3 Mendeley
Summary
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Chapter title
Classification of Arrhythmia Signals Using Hybrid Convolutional Neural Network (CNN) Model
Chapter number 6
Book title
Artificial Intelligence and Machine Learning for Healthcare
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-11154-9_6
Book ISBNs
978-3-03-111153-2, 978-3-03-111154-9
Authors

Ern, Evelyn Siao Yung, Ramli, Dzati Athiar

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Lecturer > Senior Lecturer 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Engineering 1 33%
Unknown 1 33%

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