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Machine Learning for Health Informatics

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Cover of 'Machine Learning for Health Informatics'

Table of Contents

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    Book Overview
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    Chapter 1 Machine Learning for Health Informatics
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    Chapter 2 Bagging Soft Decision Trees
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    Chapter 3 Grammars for Discrete Dynamics
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    Chapter 4 Empowering Bridging Term Discovery for Cross-Domain Literature Mining in the TextFlows Platform
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    Chapter 5 Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice
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    Chapter 6 Deep Learning Trends for Focal Brain Pathology Segmentation in MRI
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    Chapter 7 Differentiation Between Normal and Epileptic EEG Using K-Nearest-Neighbors Technique
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    Chapter 8 Survey on Feature Extraction and Applications of Biosignals
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    Chapter 9 Argumentation for Knowledge Representation, Conflict Resolution, Defeasible Inference and Its Integration with Machine Learning
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    Chapter 10 Machine Learning and Data Mining Methods for Managing Parkinson’s Disease
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    Chapter 11 Challenges of Medical Text and Image Processing: Machine Learning Approaches
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    Chapter 12 Visual Intelligent Decision Support Systems in the Medical Field: Design and Evaluation
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    Chapter 13 A Master Pipeline for Discovery and Validation of Biomarkers
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    Chapter 14 Machine Learning Solutions in Computer-Aided Medical Diagnosis
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    Chapter 15 Processing Neurology Clinical Data for Knowledge Discovery: Scalable Data Flows Using Distributed Computing
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    Chapter 16 Network-Guided Biomarker Discovery
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    Chapter 17 Knowledge Discovery in Clinical Data
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    Chapter 18 Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning
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    Chapter 19 Convolutional Neural Networks Applied for Parkinson’s Disease Identification
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    Chapter 20 Recommender Systems for Health Informatics: State-of-the-Art and Future Perspectives
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    Chapter 21 Machine Learning for In Silico Modeling of Tumor Growth
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    Chapter 22 A Tutorial on Machine Learning and Data Science Tools with Python
Attention for Chapter 22: A Tutorial on Machine Learning and Data Science Tools with Python
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Chapter title
A Tutorial on Machine Learning and Data Science Tools with Python
Chapter number 22
Book title
Machine Learning for Health Informatics
Published in
Lecture notes in computer science, December 2016
DOI 10.1007/978-3-319-50478-0_22
Book ISBNs
978-3-31-950477-3, 978-3-31-950478-0
Authors

Marcus D. Bloice, Andreas Holzinger

Editors

Andreas Holzinger

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Luxembourg 1 1%
Unknown 84 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 18%
Student > Master 14 16%
Student > Bachelor 6 7%
Researcher 5 6%
Student > Doctoral Student 4 5%
Other 15 18%
Unknown 26 31%
Readers by discipline Count As %
Computer Science 18 21%
Engineering 11 13%
Medicine and Dentistry 9 11%
Mathematics 3 4%
Environmental Science 2 2%
Other 13 15%
Unknown 29 34%