חזרה לתוצאות החיפוש

Biomedical natural language processing

להגדלת הטקסט להקטנת הטקסט
  • ספר
כותר Biomedical natural language processing / Kevin Bretonnel Cohen, University of Colorado
Dina Demner-Fushman, Lister Hill National Center for Biomedical Communication.
מהדורה 1st ed.
מוציא לאור Amsterdam : J. Benjamins Publishing Company
שנה [2014]
הערות Description based upon print version of record.
Includes bibliographical references and index.
English
הערת תוכן ותקציר ""Biomedical Natural Language Processing""
""Editorial page ""
""Title page ""
""LCC data ""
""Acknowledgments""
""Table of contents""
""List of figures""
""1. Introduction to natural language processing""
""1.1 Some definitions ""
""1.1.1 Computational linguistics ""
""1.1.2 Natural language processing ""
""1.1.3 Text mining ""
""1.1.4 Usage of these definitions in practice ""
""1.2 Levels of document and linguistic structure and their relationship to natural language processin""
""1.2.1 Document structure ""
""1.2.2 Sentences ""
""1.2.3 Tokens ""
""1.2.4 Stems and lemmata """"1.2.5 Part of speech ""
""1.2.6 Syntactic structure ""
""1.2.7 Semantics ""
""2. Historical background""
""2.1 Early work in the medical domain ""
""2.2 The emergence of the biological domain ""
""2.3 Clinical text mining ""
""2.4 Types of users of biomedical NLP systems ""
""2.5 Resources and tools ""
""US National Library of Medicine ""
""MEDLINE database ""
""Medical Subject Headings ""
""PubMed ""
""GENIA ""
""PubMed Central International ""
""2.6 Legal and ethical issues ""
""2.7 Is biomedical natural language processing effective? ""
""3. Named entity recognition""""3.1 Overview ""
""3.2 The crucial role of named entity recognition in BioNLP tasks ""
""3.3 Why gene names are the way they are ""
""3.4 An example of a rule-based gene NER system: KeX/PROPER ""
""3.5 An example of a statistical disease NER system ""
""3.6 Evaluation ""
""4. Relation extraction""
""4.1 Introduction ""
""4.1.1 Protein-protein interactions as an information extraction target ""
""4.2 Binarity of most biomedical information extraction systems ""
""4.3 Beyond simple binary relations ""
""4.4 Rule-based systems ""
""4.4.1 Co-occurrence """"4.4.2 Example rule-based systems ""
""4.4.3 Machine learning systems ""
""4.5 Relations in clinical narrative ""
""4.5.1 MedLEE ""
""4.6 SemRep ""
""4.6.1 NegEX ""
""4.7 Evaluation ""
""5. Information retrieval/document classification""
""5.1 Background ""
""5.1.1 Growth in the biomedical literature ""
""5.1.2 PubMed/MEDLINE ""
""5.2 Issues ""
""5.3 A knowledge-based system that disambiguates gene names ""
""5.4 A phrase-based search engine, with term and concept expansion and probabilistic relevance rankin""
""5.5 Full text ""
""5.6 Image and figure search """"5.7 Captions ""
""5.7.1 Evaluation ""
""6. Concept normalization""
""6.1 Gene normalization ""
""6.1.1 The BioCreative definition of the gene normalization task ""
""6.2 Building a successful gene normalization system ""
""6.2.1 Coordination and ranges ""
""6.2.2 An example system ""
""6.3 Normalization and extraction of clinically pertinent terms ""
""6.3.1 MetaMap UMLS mapping tools ""
""7. Ontologies and computational lexical semantics""
""7.1 Unified Medical Language System (UMLS) ""
""7.1.1 The Gene Ontology ""
""7.2 Recognizing ontology terms in text ""
סדרה Natural Language Processing, 1567-8202
volume 11
היקף החומר 1 online resource (172 p.)
שפה אנגלית
שנת זכויות יוצרים ©2014
מספר מערכת 997010713230905171
תצוגת MARC

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