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Data Mining: Foundations and Intelligent Paradigms

Overview of attention for book
Cover of 'Data Mining: Foundations and Intelligent Paradigms'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Advances in Intelligent Data Mining
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    Chapter 2 Temporal Pattern Mining for Medical Applications
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    Chapter 3 BioKeySpotter: An Unsupervised Keyphrase Extraction Technique in the Biomedical Full-Text Collection
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    Chapter 4 Mining Health Claims Data for Assessing Patient Risk
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    Chapter 5 Mining Biological Networks for Similar Patterns
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    Chapter 6 Estimation of Distribution Algorithms in Gene Expression Data Analysis
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    Chapter 7 Gene Function Prediction and Functional Network: The Role of Gene Ontology
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    Chapter 8 Mining Multiple Biological Data for Reconstructing Signal Transduction Networks
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    Chapter 9 Mining Epistatic Interactions from High-Dimensional Data Sets
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    Chapter 10 Knowledge Discovery in Adversarial Settings
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    Chapter 11 Analysis and Mining of Online Communities of Internet Forum Users
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    Chapter 12 Data Mining for Information Literacy
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    Chapter 13 Rule Extraction from Neural Networks and Support Vector Machines for Credit Scoring
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    Chapter 14 Using Self-Organizing Map for Data Mining: A Synthesis with Accounting Applications
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    Chapter 15 Applying Data Mining Techniques to Assess Steel Plant Operation Conditions
Attention for Chapter 4: Mining Health Claims Data for Assessing Patient Risk
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Readers on

mendeley
6 Mendeley
Summary
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Chapter title
Mining Health Claims Data for Assessing Patient Risk
Chapter number 4
Book title
Data Mining: Foundations and Intelligent Paradigms
Published by
Springer, Berlin, Heidelberg, January 2012
DOI 10.1007/978-3-642-23151-3_4
Book ISBNs
978-3-64-223150-6, 978-3-64-223151-3
Authors

Ian Duncan, Duncan, Ian

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 17%
Unknown 5 83%
Readers by discipline Count As %
Computer Science 1 17%
Unknown 5 83%

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