Description

Recognized as an essential component of Chinese culture, Traditional Chinese Medicine (TCM) is both an ancient medical system and one still used widely in China today. TCM’s independently evolved knowledge system is expressed mainly in the Chinese language and the information is frequently only available through ancient classics and confidential family records, making it difficult to utilize. The major concern in TCM is how to consolidate and integrate the data, enabling efficient retrieval and discovery of novel knowledge from the dispersed data. Computational approaches such as data mining, semantic reasoning and computational intelligence have emerged as innovative approaches for the reservation and utilization of this knowledge system. Typically, this requires an inter-disciplinary approach involving Chinese culture, computer science, modern healthcare and life sciences. This book examines the computerization of TCM information and knowledge to provide intelligent resources and supporting evidences for clinical decision-making, drug discovery, and education. Recent research results from the Traditional Chinese Medicine Informatics Group of Zhejiang University are presented, gathering in one resource systematic approaches for massive data processing in TCM. These include the utilization of modern Semantic Web and data mining methods for more advanced data integration, data analysis and integrative knowledge discovery. This book will appeal to medical professionals, life sciences students, computer scientists, and those interested in integrative, complementary, and alternative medicine.

Key Features

  • Interdisciplinary book bringing together Traditional Chinese Medicine and computer scientists
  • Introduces novel network technologies to Traditional Chinese Medicine informatics
  • Provides theory and practical examples and case studies of new techniques

Readership

Researchers and professionals working in medical fields and computer science

Table of Contents

Preface

List of Contributors

1. Overview of Knowledge Discovery in Traditional Chinese Medicine

1.1 Introduction

1.2 The State of the Art of TCM Data Resources

1.3 Review of KDTCM Research

1.4 Discussions and Future Directions

1.5 Conclusions

REFERENCES

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

2.5 MeDisco/3S System

2.6 Results

2.7 Conclusions

REFERENCES

3. MapReduce-Based Network Motif Detection for Traditional Chinese Medicine

3.1 Introduction

3.2 Related Work

3.3 MapReduce-Based Pattern Finding

3.4 Application to Prescription Compatibility Structure Detection

3.5 Conclusions

REFERENCES

4. Data Quality for Knowledge Discovery in Traditional Chinese Medicine

4.1 Introduction

4.2 Key Data Quality Dimensions in TCM

4.3 Methods to Handle Data Quality Problems

4.4 Conclusions

REFERENCES

5. Service-Oriented Data Mining in Traditional Chinese Medicine

5.1 Introduction

5.2 Related Work

5.3 System Architecture and Data Mining Service

5.4 Case Studies

5.5 Conclusions

REFERENCES

6. Semantic E-Science for Traditional Chinese Medicine

6.1 Introduction

6.2 Results

6.3 Discussion

6.4 Conclusions

6.5 Methods

REFERENCES

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 Protégé 2000: The Tool We Use

Details

No. of pages:
250
Language:
English
Copyright:
© 2012
Published:
Imprint:
Elsevier
Electronic ISBN:
9780123985194
Print ISBN:
9780123985101
Print ISBN:
9780323282727

About the editors

Zhaohui Wu

Department of Computer Science, Zhejiang University, Hangzhou, China

Huajun Chen

Department of Computer Science, Zhejiang University, Hangzhou, China

Reviews

"This book examines the computerization of TCM information and knowledge to provide intelligent resources and supporting evidences for clinical decision-making, drug discovery, and education...This book will appeal to medical professionals, life sciences students, computer scientists, and those interested in integrative, complementary, and alternative medicine."--Zentralblatt MATH 1286-1