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Machine Learning in Healthcare Informatics

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Cover of 'Machine Learning in Healthcare Informatics'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Machine Learning in Healthcare Informatics
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    Chapter 2 Wavelet-based Machine Learning Techniques for ECG Signal Analysis
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    Chapter 3 Application of Fuzzy Logic Control for Regulation of Glucose Level of Diabetic Patient
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    Chapter 4 The Application of Genetic Algorithm for Unsupervised Classification of ECG
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    Chapter 5 Pixel-based Machine Learning in Computer-Aided Diagnosis of Lung and Colon Cancer
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    Chapter 6 Understanding Foot Function During Stance Phase by Bayesian Network Based Causal Inference
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    Chapter 7 Rule Learning in Healthcare and Health Services Research
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    Chapter 8 Machine Learning Techniques for AD/MCI Diagnosis and Prognosis
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    Chapter 9 Using Machine Learning to Plan Rehabilitation for Home Care Clients: Beyond “Black-Box” Predictions
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    Chapter 10 Clinical Utility of Machine Learning and Longitudinal EHR Data
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    Chapter 11 Rule-based Computer Aided Decision Making for Traumatic Brain Injuries
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    Chapter 12 Supervised Learning Methods for Fraud Detection in Healthcare Insurance
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    Chapter 13 Feature Extraction by Quick Reduction Algorithm: Assessing the Neurovascular Pattern of Migraine Sufferers from NIRS Signals
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    Chapter 14 A Selection and Reduction Approach for the Optimization of Ultrasound Carotid Artery Images Segmentation
Attention for Chapter 4: The Application of Genetic Algorithm for Unsupervised Classification of ECG
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Chapter title
The Application of Genetic Algorithm for Unsupervised Classification of ECG
Chapter number 4
Book title
Machine Learning in Healthcare Informatics
Published by
Springer, Berlin, Heidelberg, January 2014
DOI 10.1007/978-3-642-40017-9_4
Book ISBNs
978-3-64-240016-2, 978-3-64-240017-9

Roshan Joy Martis, Hari Prasad, Chandan Chakraborty, Ajoy Kumar Ray

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 25%
Student > Bachelor 1 25%
Student > Doctoral Student 1 25%
Student > Master 1 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 25%
Earth and Planetary Sciences 1 25%
Medicine and Dentistry 1 25%
Engineering 1 25%