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Data Science for Healthcare

Overview of attention for book
Cover of 'Data Science for Healthcare'

Table of Contents

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    Book Overview
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    Chapter 1 Data Science in Healthcare: Benefits, Challenges and Opportunities
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    Chapter 2 Introduction to Classification Algorithms and Their Performance Analysis Using Medical Examples
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    Chapter 3 The Role of Deep Learning in Improving Healthcare
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    Chapter 4 Making Effective Use of Healthcare Data Using Data-to-Text Technology
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    Chapter 5 Clinical Natural Language Processing with Deep Learning
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    Chapter 6 Ontology-Based Knowledge Management for Comprehensive Geriatric Assessment and Reminiscence Therapy on Social Robots
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    Chapter 7 Assistive Robots for the Elderly: Innovative Tools to Gather Health Relevant Data
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    Chapter 8 Overview of Data Linkage Methods for Integrating Separate Health Data Sources
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    Chapter 9 A Flexible Knowledge-Based Architecture for Supporting the Adoption of Healthy Lifestyles with Persuasive Dialogs
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    Chapter 10 Visual Analytics for Classifier Construction and Evaluation for Medical Data
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    Chapter 11 Data Visualization in Clinical Practice
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    Chapter 12 Using Process Analytics to Improve Healthcare Processes
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    Chapter 13 A Multi-Scale Computational Approach to Understanding Cancer Metabolism
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    Chapter 14 Leveraging Financial Analytics for Healthcare Organizations in Value-Based Care Environments
Attention for Chapter 11: Data Visualization in Clinical Practice
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Citations

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7 Mendeley
Summary Dimensions citations
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Chapter title
Data Visualization in Clinical Practice
Chapter number 11
Book title
Data Science for Healthcare
Published by
Springer, Cham, February 2019
DOI 10.1007/978-3-030-05249-2_11
Book ISBNs
978-3-03-005248-5, 978-3-03-005249-2
Authors

Monique Hendriks, Charalampos Xanthopoulakis, Pieter Vos, Sergio Consoli, Jacek Kustra

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 29%
Student > Bachelor 2 29%
Librarian 1 14%
Unknown 2 29%
Readers by discipline Count As %
Engineering 2 29%
Computer Science 1 14%
Design 1 14%
Unknown 3 43%

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