Skip to main content

Syndromes Classification of the Active Stage of Ankylosing Spondylitis in Traditional Chinese Medicine by Cluster Analysis of Symptoms and Signs Data

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 86))

Abstract

Cluster analysis is a popular method for statistical classification for data mining. It is introduced to traditional Chinese medicine (TCM) for quantifying and normalizing the clinical practice objectively. The present study reported that TCM syndromes classification and diagnosis of 163 cases of ankylosing spondylitis (AS) active stage through cluster analysis were feasible. And 32 symptoms and signs of AS active stage were clustered and discriminated clearly. The results showed four syndromes and their corresponding therapy methods were compatible to guide TCM clinical practice, which integrated valuable experience and modern methodology preferably. Cluster analysis for AS information excavation in TCM is worthily manipulable as well as the use of which in other TCM fields.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Luke, D.A.: Getting the Big Picture in Community Science: Methods That Capture Context. Am. J. Community Psychol. 35, 185–200 (2005)

    Article  Google Scholar 

  2. Shaw, S.Y., Shah, L., Jolly, A.M., Wylie, J.L.: Identifying Heterogeneity Among Injection Drug Users: a Cluster Analysis Approach. Am. J. Public Health 98, 1430–1437 (2008)

    Article  Google Scholar 

  3. Wirfalt, A.K.E., Jeffery, R.W.: Using Cluster Analysis to Examine Dietary Patterns: Nutrient Intakes, Gender, and Weight Status Differ Across Food Pattern Clusters. J. Am. Diet. Assoc. 97, 272–279 (1997)

    Article  Google Scholar 

  4. Hearty, A.P., Gibney, M.J.: Comparison of Cluster and Principal Component Analysis Techniques to Derive Dietary Patterns in Irish Adults. Br. J. Nutr. 101, 598–608 (2009)

    Article  Google Scholar 

  5. Hennig, C.: Dissolution Point and Isolation Robustness: Robustness Criteria for General Cluster Analysis Methods. J. Multivar. Anal. 99, 1154–1176 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  6. Cheong, M.Y., Lee, H.: Determining the Number of Clusters in Cluster Aanalysis. J. Korean Stat. Soc. 37, 135–143 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  7. Younes, M., Jalled, A., Aydi, Z., Zrour, S., Korbaa, W., Salah, Z.B., Letaief, M., Bejia, I., Touzi, M., Bergaoui, N.: Socioeconomic Impact of Ankylosing Spondylitis in Tunisia. Joint Bone Spine 77, 41–46 (2010)

    Article  Google Scholar 

  8. Haywood, K.L., Garratt, A.M., Jordan, K., Dziedzic, K., Dawes, P.T.: Disease-specific, Patient-assessed Measures of Health Outcome in Ankylosing Spondylitis: Reliability, Validity and Responsiveness. Rheumatology (Oxford) 41, 1295–1302 (2002)

    Article  Google Scholar 

  9. Ward, M.M.: Quality of Life in Patients with Ankylosing Spondylitis. Rheum. Dis. Clin. North Am. 24, 815–827 (1998)

    Article  Google Scholar 

  10. Ye, R.G., Lu, Z.Y.: Internal Medicine (in Chinese). People’s Health Public House, Beijing (2004)

    Google Scholar 

  11. Zheng, Y.Y.: Clinical Research Guidelines for New Drugs of Traditional Chinese Medicine (in Chinese). China Medical Science and Technology Press, Beijing (2002)

    Google Scholar 

  12. Chen, J., Li, Y., Li, G., Li, Y.: Period Selection of Traffic Impact Analysis Based on Cluster Analysis. J. Transpn. Sys. Eng. & IT 9, 63–67 (2009)

    Google Scholar 

  13. Brandt, J., Marzo-Ortega, H., Emery, P.: Ankylosing Spondylitis: New Treatment Modalities. Best Pract. Res. Clin. Rheumatol. 20, 559–570 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yao, K., Zhang, L., Wang, J., Zhang, J. (2011). Syndromes Classification of the Active Stage of Ankylosing Spondylitis in Traditional Chinese Medicine by Cluster Analysis of Symptoms and Signs Data. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_97

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19853-3_97

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19852-6

  • Online ISBN: 978-3-642-19853-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics