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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

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Cover of 'Interactive Knowledge Discovery and Data Mining in Biomedical Informatics'

Table of Contents

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    Book Overview
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    Chapter 1 Knowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions
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    Chapter 2 Visual Data Mining: Effective Exploration of the Biological Universe
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    Chapter 3 Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining
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    Chapter 4 On the Generation of Point Cloud Data Sets: Step One in the Knowledge Discovery Process
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    Chapter 5 Adapted Features and Instance Selection for Improving Co-training
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    Chapter 6 Knowledge Discovery and Visualization of Clusters for Erythromycin Related Adverse Events in the FDA Drug Adverse Event Reporting System
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    Chapter 7 Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
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    Chapter 8 A Policy-Based Cleansing and Integration Framework for Labour and Healthcare Data
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    Chapter 9 Interactive Data Exploration Using Pattern Mining
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    Chapter 10 Resources for Studying Statistical Analysis of Biomedical Data and R
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    Chapter 11 A Kernel-Based Framework for Medical Big-Data Analytics
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    Chapter 12 On Entropy-Based Data Mining
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    Chapter 13 Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure
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    Chapter 14 Multi-touch Graph-Based Interaction for Knowledge Discovery on Mobile Devices: State-of-the-Art and Future Challenges
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    Chapter 15 Intelligent Integrative Knowledge Bases: Bridging Genomics, Integrative Biology and Translational Medicine
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    Chapter 16 Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
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    Chapter 17 Protecting Anonymity in Data-Driven Biomedical Science
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    Chapter 18 Biobanks – A Source of Large Biological Data Sets: Open Problems and Future Challenges
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    Chapter 19 On Topological Data Mining
Attention for Chapter 5: Adapted Features and Instance Selection for Improving Co-training
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Chapter title
Adapted Features and Instance Selection for Improving Co-training
Chapter number 5
Book title
Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
Published by
Springer, Berlin, Heidelberg, January 2014
DOI 10.1007/978-3-662-43968-5_5
Book ISBNs
978-3-66-243967-8, 978-3-66-243968-5
Authors

Gilad Katz, Asaf Shabtai, Lior Rokach

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 33%
Professor 1 33%
Researcher 1 33%
Student > Postgraduate 1 33%
Readers by discipline Count As %
Computer Science 3 100%
Unspecified 1 33%