Journal of Medical Systems

, Volume 34, Issue 2, pp 213–222 | Cite as

Intelligent Technique for Knowledge Reuse of Dental Medical Records Based on Case-Based Reasoning

  • Dong-xiao Gu
  • Chang-yong Liang
  • Xing-guo Li
  • Shan-lin Yang
  • Pei Zhang
Original Paper


With the rapid development of both information technology and the management of modern medical regulation, the generation of medical records tends to be increasingly intelligent. In this paper, Case-Based Reasoning is applied to the process of generating records of dental cases. Based on the analysis of the features of dental records, a case base is constructed. A mixed case retrieval method(FAIES) is proposed for the knowledge reuse of dental records by adopting Fuzzy Mathematics, which improves similarity algorithm based on Euclidian-Lagrangian Distance, and PULL&PUSH weight adjustment strategy. Finally, an intelligent system of dental cases generation (CBR-DENT) is constructed. The effectiveness of the system, the efficiency of the retrieval method, the extent of adaptation and the adaptation efficiency are tested using the constructed case base. It is demonstrated that FAIES is very effective in terms of reducing the time of writing medical records and improving the efficiency and quality. FAIES is also proven to be an effective aid for diagnoses and provides a new idea for the management of medical records and its applications.


Cased-based reasoning Dental case Retrieval Weight optimization Knowledge reuse 



This research is supported by China National Science Foundation under Grant No.70631003 and No. 70741046. The author is grateful to Professor Jian-Bo Yang (from the University of Manchester) for his valuable suggestions that led to an improved version of this article.


  1. 1.
    Li, H., Tang, S., et al., An XML Based Electronic Medical Record Integration System[C]. Advances in Web-Age Information Management. Springer: Berlin / Heidelberg, 2001, pp.160–167.Google Scholar
  2. 2.
    Guo, J., Takada, A., et al., CLAIM (Clinical Accounting Information)—An XML-Based data exchange standard for connecting electronic medical record systems to patient accounting systems. J. Med. Syst. 29(4):413–423, 2005. doi: 10.1007/s10916-005-5899-5.CrossRefGoogle Scholar
  3. 3.
    Guo, J., Takada, A., et al., Enhancement of CLAIM (Clinical Accounting Information) for a localized chinese version. J. Med. Syst. 29(5):463–471, 2005. doi: 10.1007/s10916-005-6103-7.CrossRefGoogle Scholar
  4. 4.
    Guo, J., Takada, A., et al., Enhancement of MML medical data exchange standard for a localized chinese version. J. Med. Syst. 29(5):555–567, 2005. doi: 10.1007/s10916-005-6111-7.CrossRefGoogle Scholar
  5. 5.
    Sheth, A., Agrawal, S., et al., Active Semantic Electronic Medical Record, The Semantic Web - ISWC 2006,I.Cruz et al.(Eds.):ISWC 2006,LNCS 4273, Springer Berlin / Heidelber,2006, pp.913–926.Google Scholar
  6. 6.
    Takemura, T., and Ashida, N., A study of the medical record interface to natural language processing. J. Med. Syst. 26(2):79–84, 2002. doi: 10.1023/A:1014866123819.CrossRefGoogle Scholar
  7. 7.
    Supekar, K., Marwadi, A., et al., Fuzzy Rule-Based Framework for Medical Record Validation, Intelligent Data Engineering and Automated Learning—IDEAL 2002.Springer: Berlin / Heidelberg, Vol. 2412, 2002.Google Scholar
  8. 8.
    Sharony R., Katz A., et al. A comprehensive computerized medical record system for the pacemaker cardiologic clinic. Computers in Cardiology 1989, Proceedings, Digital Object Identifier, 10.1109/CIC. 1989,130548.1989,19(22), pp.297–299.Google Scholar
  9. 9.
    Weiler, P. G., Thorpe, L., et al., An automated medical record system for a skilled nursing facility. J. Med. Syst. 11(5):367–372, 1987. doi: 10.1007/BF00996351.CrossRefGoogle Scholar
  10. 10.
    Park, C.-S., and Kim, K.-D., Preview of issues pertinent to selecting an electronic medical record for computer-aided integrated system for dental practice, Oral Radiology(Proceedings of 4th Asian Congress of Oral & Maxillo-Facial Radiology,July14–16, 2002, Kaohsiung, Taiwan), 2004,19(1).Google Scholar
  11. 11.
    Ali, Y., Falkman, G., Hallnäs, L., Jontell, M., Nazari, N., and Torgersson, O., MedView: Design and adoption of an interactive system for oral medicine. In: Hasman, A., et al. (Eds), Medical Infobahn for Europe: Proceedings of MIE2000 and GMDS2000, IOS Press, 2000.Google Scholar
  12. 12.
    Begum, S., Ahmed, M. U., Funk, P., Xiong, N., and Schéele, B., (PBM Stress Medicine AB),Similarity of Medical Cases in Health Care Using Cosine Similarity and Ontology., in the proceedings of the 5th Workshop on CBR in the Health Sciences, Springer LNCS, Bel-fast, Northern Ireland, August, 2007, pp.263–272.Google Scholar
  13. 13.
    Dressler, O., and Puppe, F., Knowledge-based diagnosis-survey and future directions. In: Puppe, F., (Ed.), Knowledge-Based Systems. Berlin / Heidelberg: Springer-verlag, 1999, pp.24–46.Google Scholar
  14. 14.
    Kim, K., and Yun, J. H., Agent-based intelligent clinical information system for persistent lifelong electronic medical record. Lee, J., and Barley, M., (Eds.), Intelligent Agents and Multi-Agent Systems. Berlin / Heidelberg: Springer-verlag, 1999, Vol. 2891, pp.194–204, 2003.Google Scholar
  15. 15.
    Bichindaritz, I., et al., Case-based reasoning in CARE-PARTNER: Gathering evidence for evidence-based medical practice. In: Smyth, B., and Cunningham, P., (Eds.), Proc of 4th European Workshop on CBR, Springer, Berlin,1998, pp. 334–345.Google Scholar
  16. 16.
    Bellazzi, R., et al., Integrating rule-based and case-based decision making in diabetic patient management. In:Althoff et al. (Eds.), Proc of 3rd Int Conference on CBR, Springer, Berlin, 1999, pp.386–400.Google Scholar
  17. 17.
    Alves, V., Neves, J., et al., Computer Tomography based Diagnosis using Extended Logic Programming and Artificial Neural Networks. Proceedings of the International NAISO Congress on Information Science Innovations ISI2001, Dubai, U.A.E., 2001.Google Scholar
  18. 18.
    Bichindaritz, I., and Montani, S., et al., Case-based reasoning in the health sciences: What’s next? Artif. Intell. Med. 36(2):127–135, 2007. doi: 10.1016/j.artmed.2005.10.008.CrossRefGoogle Scholar
  19. 19.
    Holt, A., Bichindaritz, I. ,et al., Medical applications in case-based reasoning, The Knowledge Engineering Review, Cambridge: Cambridge University Press,2005, 20: 289–292.Google Scholar
  20. 20.
    Althoff, K.-D., Bergmann, R., et al., Case-based reasoning for medical decision support tasks: the INRECA approach. Artif. Intell. Med. 12:25–41, 1998. doi: 10.1016/S0933-3657(97)00038-9.CrossRefGoogle Scholar
  21. 21.
    Alves, V., Novais, P.,et,al., Case-Based reasoning versus artificial neural networks in medical diagnosis. Hamza, M. H., (Ed.), lit. - Artificial Intelligence and Applications : proceedings of the IASTED International Conference, 3, Benalmadena, 2003.Google Scholar
  22. 22.
    Lorenzi, F., Abel, M., and Ricci, F., SISAIH: a Case-Based Reasoning Tool for Hospital Admission Authorization Management, In: Workshop on CBR in the health sciences in: vii European conference on case-based reasoning, 2004, Madrid. Workshop on CBR in the Health Sciences, 2004.Google Scholar
  23. 23.
    Yu, Y., Zheng, R., et al, Case Based Scheme for ICU , Systems Engineering-theory & Practice,2002, (3), pp.137–142.Google Scholar
  24. 24.
    Ochi-okorie, A. S., Combining medical records with case-based reasoning in a mixed paradigm design – TROPIX architecture&mplementation,ICCBR-97:international conference on case-based reasoning No2, Providence RI. ETATS-UNIS 1266, 94–103 1997.Google Scholar
  25. 25.
    Shen, Y., et al., Study of medical record repository based on framework representation and producing representation. J. South. Med. Univ. China. 26(10):1467–1470, 2006.Google Scholar
  26. 26.
    Smyth, B., and Keane, M. T., Using adaptation knowledge to retrieve and adapt design cases. Knowl. Base. Syst. 9:127–135, 1996. doi: 10.1016/0950-7051(95)01024-6.CrossRefGoogle Scholar
  27. 27.
    Therani, M., A case-based reasoning framework for workflow model management. Data Knowl. Eng. 50(1):87–115, 2004. doi: 10.1016/j.datak.2004.01.005.CrossRefGoogle Scholar
  28. 28.
    Mather, M. L., Case-based reasoning in design. Expert Syst. Appl. 6(1):34–41, 1993.Google Scholar
  29. 29.
    Watoson, I., Case-based reasoning is a methodology not a technology. Knowl. Base. Syst. 12(5,6):303–308, 1999.CrossRefGoogle Scholar
  30. 30.
    Li, C. L., Research on questionnaire design for patients satisfaction. Journal of Chinese Hospital Management. (7):473–475, 2006.Google Scholar
  31. 31.
    Zhang, B. S, and Yu, Y. L., Hybrid Similarity Measure for Retrieval in Case-based Reasoning System. Systems Engineering —Theory & Practice. (3):131–136, 2002.Google Scholar
  32. 32.
    Lee, K. W., and Khator, S. K., Case-based reasoning for cash flow forecasting using fuzzy retrieval. In:pro. of first international conference. ICCBR-95,510–519.Google Scholar
  33. 33.
    Qiao, Z., and Chen, X. H., Research on intelligence HABs early-warning system based on CBR. Ocean Technol. 9(6):31–35, 2001.MathSciNetGoogle Scholar
  34. 34.
    Lu, Y., and Wu, Y. Y. A., Decision support model of enterprise based on CBR technique. Chin. Manage. Sci. 13(2):81–87, 2005.Google Scholar
  35. 35.
    Gu, D. X., and Li, X. G., Case-based technique of reusing knowledge of business process of information system. MINI-MICRO Syst. 28(8):1439–1443, 2007.MathSciNetGoogle Scholar
  36. 36.
    Wen, W. Z., A method of ameliorative mult-objective synthetic evaluation based on 3 layer BP mode and its application. Systems Engineering —Theory & Practice. 5(5):30–34, 1999.Google Scholar
  37. 37.
    Bonzano, A., Cunningham P., and Smyth B., Using introspective learning to improve retrieval in CBR: A case study in air traffic control.IC-CBR. 291–302, 1997.Google Scholar
  38. 38.
    Chen, D., and Burrell, P., Case-based reasoning system and artificial neural networks: a Review. Neural Compute Application. 10:264–276, 2001. doi: 10.1007/PL00009897.MATHCrossRefGoogle Scholar
  39. 39.
    Lei H. G.: “Similarity analysis in die CAD system on CBR,” Proceedings of the International Conference on Agile Manufacturing, Advances in Agile Manufacturing, ICAM 2003, Beijing, Dec 4–6 2003[C], China Machine Press, 113–116.Google Scholar
  40. 40.
    Zhang, S. G., Case matching method based on scheduling in CBR. MINI-MICRO Syst. 24(4):640–642, 2003.Google Scholar
  41. 41.
    Hsu, C.-I., Predicting information systems outsourcing success using a hierarchical design of case-based reasoning. Expert Syst. Appl. 26(3):435–441, 2004. doi: 10.1016/j.eswa.2003.10.002.CrossRefGoogle Scholar
  42. 42.
    Hudson, D. L., Fuzzy logic in medical expert system. Foreign Med. Bioedical Eng. 18(3):148–154, 1995.MathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Dong-xiao Gu
    • 1
  • Chang-yong Liang
    • 1
  • Xing-guo Li
    • 1
  • Shan-lin Yang
    • 1
  • Pei Zhang
    • 2
  1. 1.School of managementHeFei University of TechnologyHeFeiPeople’s Republic of China
  2. 2.Electric Engineering Institute of PLAHeFeiPeople’s Republic of China

Personalised recommendations