《現代計算技術與中醫藥信息處理》是2012年浙江大學出版社出版的圖書，作者是吳朝暉、陳華鈞。
基本介紹
- 外文名：Modern Computational Approaches to Traditional Chinese Medicine
- 書名：現代計算技術與中醫藥信息處理
- 作者：吳朝暉 陳華鈞
- 出版日期：2012年8月1日
- 語種：英語
- ISBN：9787308084574
- 出版社：浙江大學出版社
- 頁數：233頁
- 開本：16
- 品牌：浙江大學出版社
內容簡介,圖書目錄,
內容簡介
《現代計算技術與中醫藥信息處理(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.
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.
圖書目錄
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 Discussions and Future Directions
1.5 Conclusions
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 Perspective
2.7 Conclusions
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 Extension
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 Conclusions
4 Data Quality for Knowledge Discovery in Traditional Chinese Medicine
4.1 Introduction
4.2 Key Data Quality Dimensions in TCM
4.2.1 Representation Granularity
4.2.2 Representation Consistency
4.2.3 Completeness
4.3 Methods to Handle Data Quality Problems
4.3.1 Handling Representation Granularity
4.3.2 Handling Representation Consistency
4.3.3 Handling Completeness
4.4 Conclusions
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 Conclusions
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 Conclusions
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 Relationships
7.7 Conclusions 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 Relationship Discovery from Traditional Chinese Medical Literature
13 Deriving Similarity Graphs from Traditional Chinese Medicine Linked Data on the Semantic Web
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 Discussions and Future Directions
1.5 Conclusions
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 Perspective
2.7 Conclusions
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 Extension
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 Conclusions
4 Data Quality for Knowledge Discovery in Traditional Chinese Medicine
4.1 Introduction
4.2 Key Data Quality Dimensions in TCM
4.2.1 Representation Granularity
4.2.2 Representation Consistency
4.2.3 Completeness
4.3 Methods to Handle Data Quality Problems
4.3.1 Handling Representation Granularity
4.3.2 Handling Representation Consistency
4.3.3 Handling Completeness
4.4 Conclusions
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 Conclusions
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 Conclusions
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 Relationships
7.7 Conclusions 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 Relationship Discovery from Traditional Chinese Medical Literature
13 Deriving Similarity Graphs from Traditional Chinese Medicine Linked Data on the Semantic Web
