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Modern Computational Approaches Meets Traditional Chinese Medicine.現(xiàn)代計(jì)..
- 所屬分類：
高等院校醫(yī)..
- 作者：
吳朝暉，陳華鈞，姜曉紅 著
- 出版社：
浙江大學(xué)出版社
- ISBN：9787308084574
- 出版日期：2012-8-1
-
原價(jià)：
￥120.00元
現(xiàn)價(jià)：￥83.10元
-
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圖書簡介
《現(xiàn)代計(jì)算技術(shù)與中醫(yī)藥信息處理(英文版)(精)》編著者吳朝暉、陳華鈞、姜曉紅。
TCM has an independently evolving knowledge system, which is
expressedmainly in the Chinese language. TCM knowledge discovery
and knowledge man-agement have emerged as innovative approaches for
the preservation and utilizationof this knowledge system. It aims
at the computerization of TCM information andknowledge to provide
intelligent resources and supporting evidence for clinicaldecision
making, drug discovery, and education.
目錄
Preface
1 Overview of Knowledge Discovery in Traditional Chinese Medicine
1.1 Introduction
1.2 The State of the Art of TCM Data Resources
1.2.1 Traditional Chinese Medical Literature Analysis and
Retrieval System
1.2.2 Figures and Photographs of Traditional Chinese Drug
Database
1.2.3 Database of Chinese Medical Formulae
1.2.4 Database of Chemical Composition from Chinese Herbal
Medicine
1.2.5 Clinical Medicine Database
1.2.6 TCM Electronic Medical Record Database
1.3 Review of KDTCM Research
1.3.1 Knowledge Discovery for CMF Research
1.3.2 Knowledge Discovery for CHM Research
1.3.3 Knowledge Discovery for Research of TCM Syndrome
1.3.4 Knowledge Discovery for TCM Clinical Diagnosis
1.4 Discussio and Future Directio
1.5 Conclusio
2 Integrative Mining of Traditional Chinese Medicine Literature and
MEDLINE for Functional Gene Networks
2.1 Introduction
2.2 Connecting TCM Syndrome to Modern Biomedicine by
Integrative Literature Mining
2.3 Related Work on Biomedical Literature Mining
2.4 Name Entity and Relation Extraction Methods
2.4.1 Bubble-Bootstrapping Method
2.4.2 Relation Weight Computing
2.5 MeDisco/3S System
2.6 Results
2.6.1 Functional Gene Networks
2.6.2 Functional Analysis of Genes from Syndrome Pepective
2.7 Conclusio
3 MapReduce-Based Network Motif Detection for Traditional Chinese
Medicine
3.1 Introduction
3.2 Related Work
3.3 MapReduce-Based Pattern Finding
3.3.1 MRPF Framework
3.3.2 Neighbor Vertices Finding and Pattern Initialization
3.3.3 Pattern Exteion
3.3.4 Frequency Computing
3.4 Application to Prescription Compatibility Structure Detection
3.4.1 Motifs Detection Results
3.4.2 Performance Analysis
3.5 Conclusio
4 Data Quality for Knowledge Discovery in Traditional Chinese
Medicine
4.1 Introduction
4.2 Key Data Quality Dimeio in TCM
4.2.1 Representation Granularity
4.2.2 Representation Coistency
4.2.3 Completeness
4.3 Methods to Handle Data Quality Problems
4.3.1 Handling Representation Granularity
4.3.2 Handling Representation Coistency
4.3.3 Handling Completeness
4.4 Conclusio
5 Service-Oriented Data Mining in Traditional Chinese Medicine
5.1 Introduction
5.2 Related Work
5.2.1 Traditional Data Mining Software
5.2.2 Data Mining Systems for Specific Field
5.2.3 Distributed Data Mining Platform
5.2.4 The Spora Demo
5.3 System Architecture and Data Mining Service
5.3.1 Hierarchical Structure
5.3.2 Service Operator Organization
5.3.3 User Interaction and Visualization
5.4 Case Studies
5.4.1 Case 1 : Domain-Driven KDD Support for TCM
5.4.2 Case 2: Data Mining Based on Distributed Resources
5.4.3 Case 3: Data Mining Process as a Service
5.5 Conclusio
6 Semantic E-Science for Traditional Chinese Medicine
6.1 Introduction
6.2 Results
6.2.1 System Architecture
6.2.2 TCM Domain Ontology
6.2.3 DartMapping
6.2.4 DartSearch
6.2.5 DartQuery
6.2.6 TCM Service Coordination
6.2.7 Knowledge Discovery Service
6.2.8 DartFlow
6.2.9 TCM Collaborative Research Scenario
6.2.10 Task-Driven Information Allocation
6.2.11 Collaborative Information Sharing
6.2.12 Scientific Service Coordination
6.3 Discussion
6.4 Conclusio
6.5 Methods
6.5.1 TCM OntoLogy Engineering
6.5.2 View-Based Semantic Mapping
6.5.3 Semantic-Based Service Matchmaking
7 Ontology Development for Unified Traditional Chinese Medical
Language System
7.1 Introduction
7.2 The Principle and Knowledge System of TCM
7.3 What Is an Ontology?
7.4 Protege 2000: The Tool We Use
7.5 Ontology Design and Development for UTCMLS
7.5.1 Methodology of Ontology Development
7.5.2 Knowledge Acquisition
7.5.3 Integrating and Merging of TCM Ontology
7.6 Results
7.6.1 The Core Top-Level Categories
7.6.2 Subontologies and the Hierarchical Structure
7.6.3 Concept Structure
7.6.4 Semantic Structure
7.6.5 Semantic Types and Semantic Relatiohips
7.7 Conclusio Causal Knowledge Modeling for Traditional Chinese
Medicine Using OWL 2
8 Causal Knowledge Modeling for Traditional Chinese Medicine Using
OWL 2
9 Dynamic Subontology Evolution for Traditional Chinese Medicine
Web Ontology
10 Semantic Association Mining for Traditional Chinese Medicine
11 Semantic-Based Database Integration for Traditional Chinese
Medicine
12 Probabilistic Semantic Relatiohip Discovery from Traditional
Chinese Medical Literature
13 Deriving Similarity Graphs from Traditional Chinese Medicine
Linked Data on the Semantic Web
《現(xiàn)代計(jì)算技術(shù)與中醫(yī)藥信息處理(英文版)(精)》編著者吳朝暉、陳華鈞、姜曉紅。 TCM has an independently evolving knowledge system, which is expressedmainly in the Chinese language. TCM knowledge discovery and knowledge man-agement have emerged as innovative approaches for the preservation and utilizationof this knowledge system. It aims at the computerization of TCM information andknowledge to provide intelligent resources and supporting evidence for clinicaldecision making, drug discovery, and education.
Preface
1 Overview of Knowledge Discovery in Traditional Chinese Medicine
1.1 Introduction
1.2 The State of the Art of TCM Data Resources
1.2.1 Traditional Chinese Medical Literature Analysis and
Retrieval System
1.2.2 Figures and Photographs of Traditional Chinese Drug
Database
1.2.3 Database of Chinese Medical Formulae
1.2.4 Database of Chemical Composition from Chinese Herbal
Medicine
1.2.5 Clinical Medicine Database
1.2.6 TCM Electronic Medical Record Database
1.3 Review of KDTCM Research
1.3.1 Knowledge Discovery for CMF Research
1.3.2 Knowledge Discovery for CHM Research
1.3.3 Knowledge Discovery for Research of TCM Syndrome
1.3.4 Knowledge Discovery for TCM Clinical Diagnosis
1.4 Discussio and Future Directio
1.5 Conclusio
2 Integrative Mining of Traditional Chinese Medicine Literature and
MEDLINE for Functional Gene Networks
2.1 Introduction
2.2 Connecting TCM Syndrome to Modern Biomedicine by
Integrative Literature Mining
2.3 Related Work on Biomedical Literature Mining
2.4 Name Entity and Relation Extraction Methods
2.4.1 Bubble-Bootstrapping Method
2.4.2 Relation Weight Computing
2.5 MeDisco/3S System
2.6 Results
2.6.1 Functional Gene Networks
2.6.2 Functional Analysis of Genes from Syndrome Pepective
2.7 Conclusio
3 MapReduce-Based Network Motif Detection for Traditional Chinese
Medicine
3.1 Introduction
3.2 Related Work
3.3 MapReduce-Based Pattern Finding
3.3.1 MRPF Framework
3.3.2 Neighbor Vertices Finding and Pattern Initialization
3.3.3 Pattern Exteion
3.3.4 Frequency Computing
3.4 Application to Prescription Compatibility Structure Detection
3.4.1 Motifs Detection Results
3.4.2 Performance Analysis
3.5 Conclusio
4 Data Quality for Knowledge Discovery in Traditional Chinese
Medicine
4.1 Introduction
4.2 Key Data Quality Dimeio in TCM
4.2.1 Representation Granularity
4.2.2 Representation Coistency
4.2.3 Completeness
4.3 Methods to Handle Data Quality Problems
4.3.1 Handling Representation Granularity
4.3.2 Handling Representation Coistency
4.3.3 Handling Completeness
4.4 Conclusio
5 Service-Oriented Data Mining in Traditional Chinese Medicine
5.1 Introduction
5.2 Related Work
5.2.1 Traditional Data Mining Software
5.2.2 Data Mining Systems for Specific Field
5.2.3 Distributed Data Mining Platform
5.2.4 The Spora Demo
5.3 System Architecture and Data Mining Service
5.3.1 Hierarchical Structure
5.3.2 Service Operator Organization
5.3.3 User Interaction and Visualization
5.4 Case Studies
5.4.1 Case 1 : Domain-Driven KDD Support for TCM
5.4.2 Case 2: Data Mining Based on Distributed Resources
5.4.3 Case 3: Data Mining Process as a Service
5.5 Conclusio
6 Semantic E-Science for Traditional Chinese Medicine
6.1 Introduction
6.2 Results
6.2.1 System Architecture
6.2.2 TCM Domain Ontology
6.2.3 DartMapping
6.2.4 DartSearch
6.2.5 DartQuery
6.2.6 TCM Service Coordination
6.2.7 Knowledge Discovery Service
6.2.8 DartFlow
6.2.9 TCM Collaborative Research Scenario
6.2.10 Task-Driven Information Allocation
6.2.11 Collaborative Information Sharing
6.2.12 Scientific Service Coordination
6.3 Discussion
6.4 Conclusio
6.5 Methods
6.5.1 TCM OntoLogy Engineering
6.5.2 View-Based Semantic Mapping
6.5.3 Semantic-Based Service Matchmaking
7 Ontology Development for Unified Traditional Chinese Medical
Language System
7.1 Introduction
7.2 The Principle and Knowledge System of TCM
7.3 What Is an Ontology?
7.4 Protege 2000: The Tool We Use
7.5 Ontology Design and Development for UTCMLS
7.5.1 Methodology of Ontology Development
7.5.2 Knowledge Acquisition
7.5.3 Integrating and Merging of TCM Ontology
7.6 Results
7.6.1 The Core Top-Level Categories
7.6.2 Subontologies and the Hierarchical Structure
7.6.3 Concept Structure
7.6.4 Semantic Structure
7.6.5 Semantic Types and Semantic Relatiohips
7.7 Conclusio Causal Knowledge Modeling for Traditional Chinese
Medicine Using OWL 2
8 Causal Knowledge Modeling for Traditional Chinese Medicine Using
OWL 2
9 Dynamic Subontology Evolution for Traditional Chinese Medicine
Web Ontology
10 Semantic Association Mining for Traditional Chinese Medicine
11 Semantic-Based Database Integration for Traditional Chinese
Medicine
12 Probabilistic Semantic Relatiohip Discovery from Traditional
Chinese Medical Literature
13 Deriving Similarity Graphs from Traditional Chinese Medicine
Linked Data on the Semantic Web
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