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Machine Learning in Healthcare Informatics

Overview of attention for book
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 1: Introduction to Machine Learning in Healthcare Informatics
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Citations

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Chapter title
Introduction to Machine Learning in Healthcare Informatics
Chapter number 1
Book title
Machine Learning in Healthcare Informatics
Published by
Springer, Berlin, Heidelberg, January 2014
DOI 10.1007/978-3-642-40017-9_1
Book ISBNs
978-3-64-240016-2, 978-3-64-240017-9
Authors

Pradeep Chowriappa, Sumeet Dua, Yavor Todorov

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Unknown 100 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 21%
Student > Master 16 16%
Researcher 13 13%
Student > Doctoral Student 5 5%
Student > Postgraduate 4 4%
Other 18 18%
Unknown 24 24%
Readers by discipline Count As %
Computer Science 37 37%
Medicine and Dentistry 15 15%
Engineering 12 12%
Nursing and Health Professions 4 4%
Business, Management and Accounting 3 3%
Other 4 4%
Unknown 26 26%