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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

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    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
  20. Altmetric Badge
    Chapter 19 On Topological Data Mining
Attention for Chapter 7: Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
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Chapter title
Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
Chapter number 7
Book title
Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
Published in
Lecture notes in computer science, January 2014
DOI 10.1007/978-3-662-43968-5_7
Book ISBNs
978-3-66-243967-8, 978-3-66-243968-5
Authors

Turkay, C., Cagatay Turkay, Fleur Jeanquartier, Andreas Holzinger, Helwig Hauser

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Austria 3 7%
Singapore 1 2%
Unknown 38 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 21%
Student > Ph. D. Student 7 17%
Professor > Associate Professor 5 12%
Student > Bachelor 4 10%
Researcher 3 7%
Other 9 21%
Unknown 5 12%
Readers by discipline Count As %
Computer Science 25 60%
Business, Management and Accounting 2 5%
Engineering 2 5%
Unspecified 1 2%
Agricultural and Biological Sciences 1 2%
Other 4 10%
Unknown 7 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 April 2016.
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#20,326,948
of 22,870,727 outputs
Outputs from Lecture notes in computer science
#6,989
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Outputs of similar age
#265,198
of 305,631 outputs
Outputs of similar age from Lecture notes in computer science
#236
of 280 outputs
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So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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