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Medical Informatics

Overview of attention for book
Cover of 'Medical Informatics'

Table of Contents

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    Book Overview
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    Chapter 1 Knowledge Management, Data Mining, and Text Mining in Medical Informatics
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    Chapter 2 Mapping Medical Informatics Research
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    Chapter 3 Bioinformatics Challenges and Opportunities
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    Chapter 4 Managing Information Security and Privacy in Healthcare Data Mining
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    Chapter 5 Ethical and Social Challenges of Electronic Health Information
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    Chapter 6 Medical Concept Representation
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    Chapter 7 Characterizing Biomedical Concept Relationships
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    Chapter 8 Biomedical Ontologies
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    Chapter 9 Information Retrieval and Digital Libraries
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    Chapter 10 Modeling Text Retrieval in Biomedicine
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    Chapter 11 Public Access to Anatomic Images
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    Chapter 12 3D Medical Informatics
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    Chapter 13 Infectious Diseaxe Informatics and Outbreak detection
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    Chapter 14 Semantic Interpretation for the Biomedical Research Literature
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    Chapter 15 Semantic Text Parsing for Patient Records
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    Chapter 16 Identification of Biological Relationships from Text Documents
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    Chapter 17 Creating, Modeling, and Visualizing Metabolic Networks
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    Chapter 18 Gene Pathway Text Mining and Visualization
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    Chapter 19 The Genomic Data Mine
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    Chapter 20 Exploratory Genomic Data Analysis
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    Chapter 21 Joint Learning Using Multiple Types of Data and Knowledge
Attention for Chapter 15: Semantic Text Parsing for Patient Records
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Chapter title
Semantic Text Parsing for Patient Records
Chapter number 15
Book title
Medical Informatics
Published by
Springer, Boston, MA, January 2005
DOI 10.1007/0-387-25739-x_15
Book ISBNs
978-0-387-24381-8, 978-0-387-25739-6
Authors

Carol Friedman, Friedman, Carol

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 6%
Netherlands 1 2%
Sweden 1 2%
Australia 1 2%
Denmark 1 2%
United Kingdom 1 2%
Unknown 40 83%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 29%
Researcher 12 25%
Student > Ph. D. Student 11 23%
Professor 4 8%
Other 3 6%
Other 3 6%
Unknown 1 2%
Readers by discipline Count As %
Computer Science 28 58%
Medicine and Dentistry 7 15%
Agricultural and Biological Sciences 3 6%
Chemistry 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 3 6%
Unknown 3 6%