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Artificial Intelligence in Medical Imaging

Overview of attention for book
Cover of 'Artificial Intelligence in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Game Changers in Radiology
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    Chapter 2 The Role of Medical Image Computing and Machine Learning in Healthcare
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    Chapter 3 A Deeper Understanding of Deep Learning
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    Chapter 4 Deep Learning and Machine Learning in Imaging: Basic Principles
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    Chapter 5 How to Develop Artificial Intelligence Applications
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    Chapter 6 A Standardised Approach for Preparing Imaging Data for Machine Learning Tasks in Radiology
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    Chapter 7 The Value of Structured Reporting for AI
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    Chapter 8 Artificial Intelligence in Medicine: Validation and Study Design
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    Chapter 9 Enterprise Imaging
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    Chapter 10 Imaging Biomarkers and Imaging Biobanks
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    Chapter 11 Applications of AI Beyond Image Interpretation
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    Chapter 12 Artificial Intelligence and Computer-Assisted Evaluation of Chest Pathology
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    Chapter 13 Cardiovascular Diseases
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    Chapter 14 Deep Learning in Breast Cancer Screening
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    Chapter 15 Neurological Diseases
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    Chapter 16 The Role of AI in Clinical Trials
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    Chapter 17 Quality and Curation of Medical Images and Data
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    Chapter 18 Does Future Society Need Legal Personhood for Robots and AI?
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    Chapter 19 The Role of an Artificial Intelligence Ecosystem in Radiology
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    Chapter 20 Advantages, Challenges, and Risks of Artificial Intelligence for Radiologists
Overall attention for this book and its chapters
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2 news outlets
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2 blogs
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1 policy source
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400 X users
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3 Facebook pages

Citations

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107 Dimensions

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245 Mendeley
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Title
Artificial Intelligence in Medical Imaging
Published by
Springer International Publishing, February 2019
DOI 10.1007/978-3-319-94878-2
ISBNs
978-3-31-994877-5, 978-3-31-994878-2
Editors

Ranschaert, Erik R., Morozov, Sergey, Algra, Paul R.

X Demographics

X Demographics

The data shown below were collected from the profiles of 400 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 245 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 11%
Student > Master 25 10%
Student > Bachelor 24 10%
Student > Ph. D. Student 22 9%
Lecturer 14 6%
Other 43 18%
Unknown 91 37%
Readers by discipline Count As %
Medicine and Dentistry 38 16%
Computer Science 29 12%
Engineering 23 9%
Nursing and Health Professions 15 6%
Social Sciences 8 3%
Other 39 16%
Unknown 93 38%