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Support to self-diagnosis with awareness

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Abstract

In this research, we proposed an awareness system for self-diagnosis support. The system contains two circular layers. The inner layer is called disease awareness layer, which could be aware of the user's condition, and gives a diagnosis conclusion. The outer layer is the health awareness layer. It takes diagnosis conclusion as the input, generates possible solutions and exchanges information with the user. The user is not controlled by health awareness layer directly, but performs as an executant. Therefore, the system could understand most user conditions, show proper diagnosis and motivate users to adapt their behavior from sickness to health.

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References

  1. Grace B, Bennett B, Hu F (2013) "Improve Health Care", Cyber-Physical Systems: Integrated Computing and Engineering Design

  2. Swayne LE, Duncan WJ, Ginter PM (2012) "Strategic management of health care organizations", Wiley

  3. Shi L, Singh DA (2012) "Essentials of the United States health care system", Jones & Bartlett Publishers

  4. Korenstein D, Falk R, Howell EA (2012) Overuse of health care services in the United States: an understudied problem. Arch Intern Med 172(2):171

    Article  Google Scholar 

  5. Mayo Clinic: http://www.mayoclinic.com

  6. Health-EU: http://ec.europa.eu/health-eu/index_en.htm

  7. National Health Service: http://www.nhs.uk/Pages/HomePage.aspx

  8. 39 Health Net (Chinese): http://www.39.net/

  9. Wagholikar KB, Sundararajan V, Deshpande AW (2012) Modeling paradigms for medical diagnostic decision support: a survey and future directions. J Med Syst 36.5:3029–49

    Google Scholar 

  10. Pearl J (2001) Bayesian Networks Handbook of Brain Theory and Neural Networks, MIT Press

  11. Kappen B, Wiegerinck W, Akay E (2003) Promedas: a clinical diagnostic decision support system. In: Proceedings of the 15th Belgian-Dutch Conference on Artificial Intelligence, pp 23–24

  12. Scholten P, Ji J (2012) Semantic Information System for Health Care. In: Proceedings of East Meets West on Innovation and Entrepreneurship (EASTWEST2012), pp 427–440

  13. Zhao QF (2012) An Introduction to Computational Awareness. In: Proceedings of International Conference on Awareness and Technology, Korea University, Seoul, Aug

  14. Sawada Y (2013) Subjectivity and awareness. Int J Mach Learn Cybern

  15. Tsai CW, Pelov A, Chiang MC, Yang CS, Hong TP (2013) Computational awareness for smart grid: a review. Int J Mach Learn Cybern

  16. Kainulainen A, Turunen M, Hakulinen J (2009) Awareness Information with Speech and Sound. Awareness Systems Human-Computer Interaction Series, pp 231–256

  17. Gao W, Li Q, Zhao B (2012) Social-aware multicast in disruption-tolerant networks. IEEE/ACM Transactions on Networking (TON). 20(5):1553–66

    Google Scholar 

  18. Zhong Z, Liu Z, Li C, Guan Y (2012) Event ontology reasoning based on event class influence factors. Int J Mach Learn Cybern 3(2):133–139

    Google Scholar 

  19. Staab S, Studer R (2009) Handbook on ontologies, Springer

  20. World Wide Web Consortium (W3C) (2011) W3C Semantic Web Activity November 7

  21. Simple HTML DOM: http://simplehtmldom.sourceforge.net

  22. Zorgkaart Netherland: http://www.zorgkaartnederland.nl

  23. Eastin: http://www.eastin.eu

  24. Apache+MySQL: http://www.apachefriends.org/en/xampp.html

  25. Horridge M, Bechhofer S (2009) The OWL API: A Java API for working with owl 2 ontologies. In: Proceedings of the 6th International Workshop on OWL: Experiences and Directions (OWLED 2009), volume 529 of CEUR Workshop Proceedings

  26. FactPlusPlus: http://code.google.com/p/factplusplus

  27. http://labtestsonline.org

  28. Ji J, Chan TYT, Zhao Q (2010) Clustering large sparse text data: a comparative advantage approach. JIP 18:242–251

    Google Scholar 

  29. Hall P, Park BU (2008) Samworth RJ Choice of neighbor order in nearest-neighbor classification. Ann Stat 36(5):2135–2152

    Google Scholar 

Download references

Acknowledgments

This research was supported by Promotive Research Funds for Excellent Young and Middle-aged Scientists of Shandong Province (2012BSE27173) and Science and Technology Program of Higher Education of Shandong Province (J13LM60).

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Authors and Affiliations

  1. Jining University, Qufu, Shandong, China

    Jie Ji

  2. Scholten Consultancy, Amsterdam, The Netherlands

    Peter Scholten

  3. Aizu, Fukushima, Japan

    Qiangfu Zhao

Authors
  1. Jie Ji
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  2. Peter Scholten
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  3. Qiangfu Zhao
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Correspondence to Jie Ji.

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Ji, J., Scholten, P. & Zhao, Q. Support to self-diagnosis with awareness. Int. J. Mach. Learn. & Cyber. 5, 647–658 (2014). https://doi.org/10.1007/s13042-013-0209-x

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  • DOI: https://doi.org/10.1007/s13042-013-0209-x

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