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Multi-Modal Reasoning medical diagnosis system integrated with probabilistic reasoning

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Abstract

In this paper, a Multi Modal Reasoning (MMR) method integrated with probabilistic reasoning is proposed for the diagnosis support module of the open eHealth platform. MMR is based on both Rule Based Reasoning (RBR) and Case Based Reasoning (CBR). It is not only applied to the identification of diseases and syndromes based on medical guidelines, but also deals with exceptional cases and individual therapies in order to improve diagnostic accuracy. Moreover, a new rule expression frame is introduced to deal with uncertainty, which can represent and process vague, imprecise, and incomplete information. Furthermore, this system is capable of updating the attributes of rules and inducing rules with a small data sample.

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References

  1. X. Dong, R. Dai. Traditional Chinese Medicine from the point of view of System Science, Clinical Acupuncture and Oriental Medicine, vol. 4, no. 1, pp. 34–37, 2003.

    Article  Google Scholar 

  2. J. Zhu, R. Ken. Chinese medicine and complexity, Clinical Acupuncture and Oriental Medicine, vol. 3, no. 2, pp. 77–91, 2002.

    Article  Google Scholar 

  3. Z. Yanfu. Diagnostics of Traditional Chinese Medicine. Publishing House of Shanghai University of Traditional Chinese Medicine, Shanghai, PRC 2002.

    Google Scholar 

  4. M. He, X. Yan, J. Zhou, G. Xie, Traditional Chinese Medicine Database and Application on the Web, Journal of Chemical Informatics and Computer Sciences, vol. 41, no. 2, pp. 273–7, 2001.

    Article  Google Scholar 

  5. Y. Liu, Y. Sun, China traditional Chinese Medicine (TCM) Patent Database, World Patent Information, vol. 26, no. 1, pp. 91–96, 2004.

    Article  MathSciNet  Google Scholar 

  6. Y. Li, X. Yan, G. Xie, P. Liu, W. Tang, J. Zhou. The database of ready-prepared Chinese medicine, Clinical Acupuncture and Oriental Medicine, vol. 2, no. 4, pp. 209–217, 2001.

    Article  Google Scholar 

  7. X. Wang, H. Qu, P. Liu, Y. Cheng, A self-learning expert system for diagnosis in traditional Chinese medicine, Expert Systems with Applications, vol. 26, no. 4, pp. 557–566, 2004.

    Article  Google Scholar 

  8. C. Cao, H. Wang, Y. Sui. Knowledge modeling and acquisition of traditional Chinese herbal drugs and formulae from text, Artificial Intelligence in Medicine, vol. 32, no. 1, pp. 3–13, 2004.

    Article  Google Scholar 

  9. J. Tian, K. Yeung, X. Chen. Intelligent Information Support System for Chinese Medicine using rule-based and case-based reasoning, In Proceedings of the International Conference on Computational Science and its Applications (ICCSA 2005), Singapore, 2005.

  10. K. Yeung, J. Tian, X. Chen, Extracting Knowledge from Free Text and Knowledge Discovery in Databases for Chinese Medicine, In Proceedings of the International Conference on Computational Science and its Applications (ICCSA 2005), Singapore, 2005.

  11. J. Tian, K. Yeung, X. Chen, J. Wu, J. Huang. An Open e-Health platform for Chinese Medicine, In Proceedings of the 10th Chinese Automation & Computing Society Conference, Liverpool, England, 2004.

  12. K. Yeung, J. Tian, X. Chen, X. Wu, J. Huang. Accuracy assessment based on indirect and direct information for Chinese Medicine, In Proceedings of the 10th Chinese Automation & Computing Society Conference, Liverpool, England, 2004.

  13. P. Hanzlicek, J. Spidlen, H. Heroutova, M. Nagy. User interface of MUDR electronic health record, International Journal of Medical Informatics, vol. 74, no. 2–4, pp. 221–227, 2005.

    Article  Google Scholar 

  14. J. L. Kolodner. Case-Based Reasoning. Morgan Kaufmann Publishers Inc., San Mateo, CA, 1993.

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of Mechanical, Materials, Manufacturing, Engineering and Management, University of Nottingham, University Park, NG7 2RD, UK

    Jia Tian & Xun Chen

  2. Exhibition Road Hospital, Xi Cheng District, Beijing, 100037, PRC

    Sheng-Ping Dong

Authors
  1. Jia Tian
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  2. Xun Chen
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  3. Sheng-Ping Dong
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Corresponding author

Correspondence to Jia Tian.

Additional information

Jia Tian received her BSc degree from China University of Mining and Technology (CUMT), Beijing, China in 2002. She is currently pursuing her PhD at the University of Nottingham, United Kingdom. Her research interests include expert system, artificial intelligence and data mining, especially Medical Decision Support System, Case Based Reasoning, Rule Based Reasoning and Bayesian Networks.

Xun Chen obtained his B. Eng. from Fuzhou University. He received his M. Sc. from Zhejiang University and his Ph. D from Liverpool John Moores University. He has been a visiting professor to Fuzhou University since 2001. He specialises in advanced manufacturing technology including application of computer science, mechatronics and artificial intelligence to broad engineering application. He has published more than 100 research papers. Dr Chen is a founder member of the International Committee of Abrasive Technology. Before his employment at Nottingham, Dr Chen was a lecturer of Mechanical Engineering at the University of Dundee. Prior to that, he was a research fellow, a Royal Society Royal Fellow at Liverpool John Moores University and a lecturer at Fuzhou University.

Sheng-Ping Dong graduated from China University of Traditional Chinese Medicine, Beijing, China. She is an attending doctor of Traditional Chinese Medicine with many years clinical experience in Exhibition Road Hospital, Beijing, China.

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Tian, J., Chen, X. & Dong, SP. Multi-Modal Reasoning medical diagnosis system integrated with probabilistic reasoning. Int J Automat Comput 2, 134–143 (2005). https://doi.org/10.1007/s11633-005-0134-x

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  • DOI: https://doi.org/10.1007/s11633-005-0134-x

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