Skip to main content
SpringerLink
Log in

An efficient approach to representing and mining knowledge from Qing court medical records

  • Research Article
  • Published:
Frontiers of Computer Science in China Aims and scope Submit manuscript

Abstract

Research on Qing Court Medical Records (RQCMR) is a large-volume book which was edited and annotated by the sixth co-author Keji, Chen and his colleagues, and consists of all the medical records of imperial families and aristocrats of the Qing dynasty. To reveal and utilize their high value both in traditional Chinese medicine research and modern clinical practice, we have developed a method of transforming the Qing Court Medical Records (QCMR) into a computer-readable, structured representation, so that statistical analysis and data mining can be accurately performed. The method consists of a frame ontology based medical language, called MedL, for representing QCMR, a parser for compiling MedL frames into a database, and an explorative pattern mining technique. With this method the entire RQCMR volume is transformed into a database and medical patterns may be mined from the database.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Chen K. Research on Qing Court Medical Records, Beijing: Science Press, 2009

    Google Scholar 

  2. Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases. In: Proceedings of 1993 ACM SIGMOD International Conference on Management of Data. 1993, 207–216

  3. Omiecinski E R. Alternative interest measures for mining associations in databases. IEEE Transactions on Knowledge and Data Engineering, 2003, 15(1): 57–69

    Article  MathSciNet  Google Scholar 

  4. Wang J, Cui M. Applications of KDD in traditional Chinese medical formulae. Chinese Journal of Information on Traditional Chinese Medicine, 2008, 15(3): 103–104

    Google Scholar 

  5. Zhang L, Lu L. Traditional Chinese medicine data mining platform based on strategy pattern. Journal of Computer Systems & Applications, 2010, 19(11): 5–9

    Google Scholar 

  6. Verta O, Mastroianni C, Talia D. A super-peer model for resource discovery services in large-scale grids. Future Generation Computer Systems, 2005, 21(8): 1235–1248

    Article  Google Scholar 

  7. Karger D, Ruhl M. Simple efficient load balancing algorithms for peer-to-peer systems. In: Proceedings of the 16th Annual ACM Symposium on Parallelism in Algorithm and Architectures. 2004, 36–40

  8. Fikes R, Kehler T. The role of frame-based representation in reasoning. Communications of the ACM, 1985, 28(9): 904–920

    Article  Google Scholar 

  9. Cao C, Wang H, Sui Y. Knowledge modeling and acquisition of traditional Chinese herbal drugs and formulae from text. Artificial Intelligence in Medicine, 2004, 32(1): 3–13

    Article  Google Scholar 

  10. Cao C, Sui Y. Building an ontology and knowledge base of the human meridian-collateral system. In: Proceedings of 25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. 2005, 195–208

  11. Wang H, Cao C, Gao Y. Design and implementation of a system for ontology-mediated knowledge acquisition from semi-structured text. Journal of Computer, 2005, 28(12): 2010–2018

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School, Chinese Academy of Sciences, Beijing, 100190, China

    Weimin Wang, Cong Cao & Tao Hou

  2. Cardiovascular Department of Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, China

    Jingchun Zhang, Yue Liu & Keji Chen

  3. School of Computer Science & Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, China

    Weimin Wang

Authors
  1. Weimin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jingchun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cong Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tao Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yue Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Keji Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Weimin Wang or Jingchun Zhang.

Additional information

Weimin Wang received his PhD in 2008 at the Graduate University of the Chinese Academy of Sciences. Wang is now working as a postdoc at the Institute of Computing Technology of the Chinese Academy of Sciences and a lecturer at Jiangsu University of Science and Technology. His research interests include data mining, natural language processing, information retrieval and ontology engineering.

Jingchun Zhang received her PhD in 2007 at the China Academy of Chinese Medical Sciences (CACMS), and then continued as a member of Post Doctorate staff from 2008–2010. Now she is working as Medical Professor and supervisor to Masters Degree applicants in the Cardiology Research Center of Xiyuan Hospital of CACMS. Her research interests include medical knowledge mining and clinical medicine.

Cong Cao is pursuing his Masters in the Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Science. His current research interests include data mining and common sense knowledge acquisition.

Tao Hou, majored in Software Engineering, graduated from Beijing Institute of Technology for his Bachelors in 2010. Hou is now pursuing his Masters degree in the Institute of CG & CAD, school of software, Tsinghua University. His research interests are image processing and data visualization.

Yue Liu received his Masters in Medicine at Beijing university of Chinese medicine in 2008, and is now pursuing his Doctors degree in China Academy of Chinese Medical Sciences. His research interests include medical knowledge mining and clinical medicine.

Keji Chen is an Academician of the Chinese Academy of Sciences and Principal Researcher of CACMS. He received an honorary PhD from the Hong Kong Baptist University in 2004. He is now working in the Cardiology Research Center of Xiyuan Hospital of China Academy of Chinese Medical Sciences. His research interests include medical knowledge mining and clinical medicine.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, W., Zhang, J., Cao, C. et al. An efficient approach to representing and mining knowledge from Qing court medical records. Front. Comput. Sci. China 5, 395–404 (2011). https://doi.org/10.1007/s11704-011-1021-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11704-011-1021-y

Keywords

Search

Navigation