Skip to main content
SpringerLink
Log in
Book cover

Conference on Artificial Intelligence in Medicine in Europe

AIME 1997: Artificial Intelligence in Medicine pp 319–330Cite as

Temporal Abstractions for diabetic patients management

  • Temporal Reasoning and Planning
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1211))

Abstract

This paper outlines how Temporal Abstractions can be used to analyze and interpret longitudinal data coming from diabetic patients monitoring. We use temporal abstraction mechanisms to provide an abstract description of the patient's state useful to interpret the therapeutic response to the current protocol and to provide proper suggestions.

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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Allen J. F.: Towards a general theory of action and time. Artificial Intelligence 23 (1984) 123–154

    Google Scholar 

  2. Bellazzi, R., Cobelli, C., Gomez, E., Stefanelli, M.: The T-IDDM project: Telematic management of Insulin Dependent Diabetes Mellitus. Proc. of Health Telematics '95, M. Bracale, F. Denoth eds., Ischia (1995) 271–276.

    Google Scholar 

  3. Bellazzi, R., Larizza, C., Riva, A.: Cooperative Intelligent Data Analysis: an application to diabetic patients management. Proc. of IDAMAP '96, a workshop of ECAI 96, Budapest (1996) 1–6

    Google Scholar 

  4. Deutsch, T., Lehmann, E.D., Carson, E.R., Roudsari, A.V., Hopkins, K.D., Sönksen, P.: Time series analysis and control of blood glucose levels in diabetic patients. Comp. Meth. and Programs in Biomed. 41 (1994) 167–182.

    Google Scholar 

  5. The Diabetes Control and Complication Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus, The New England Journal of Medicine 14-329 (1993) 977–986

    Google Scholar 

  6. Larizza, C., Bernuzzi, G., Stefanelli, M.: A General Framework for Building Patient Monitoring Systems. Lecture Notes in Artificial Intelligence, P. Barahona, M. Stefanelli and J. Wyatt eds., Springer Verlag, Berlin (1995) 91–102

    Google Scholar 

  7. Keravnou, E.: Temporal asbtraction of medical data: Deriving periodicity. Proceedings of IDAMAP '96, a workshop of ECAI 96, Budapest (1996) 43–60

    Google Scholar 

  8. Miksch, S., Horn, W., Popow, C., Paky, F.: Therapy Planning Using Qualitative Trend Descriptions. Lecture Notes in Artificial Intelligence, P. Barahona, M. Stefanelli and J. Wyatt eds., Springer Verlag, Berlin (1995) 197–208

    Google Scholar 

  9. Riva, A., Bellazzi, R.: High level control strategies for diabetes therapy. Lecture Notes in Artificial Intelligence, P. Barahona, M. Stefanelli and J. Wyatt eds., Springer Verlag, Berlin (1995) 185–196

    Google Scholar 

  10. Riva, A., Bellazzi, R.: Learning Temporal Probabilistic Causal Models from Longitudinal Data, Artificial Intelligence in Medicine 8 (1996) 217–234

    Google Scholar 

  11. Shahar, Y., Musen, M.A.: Knowledge-Based Temporal Abstraction in Clinical Domains. Artificial Intelligence in Medicine 8 (1996) 267–298

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Informatica e Sistemistica, Università di Pavia, Pavia, Italy

    Cristiana Larizza & Riccardo Bellazzi

  2. IRCCS Policlinico S.Matteo, Pavia, Italy

    Alberto Riva

Authors
  1. Cristiana Larizza
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Riccardo Bellazzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alberto Riva
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Elpida Keravnou Catherine Garbay Robert Baud Jeremy Wyatt

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Larizza, C., Bellazzi, R., Riva, A. (1997). Temporal Abstractions for diabetic patients management. In: Keravnou, E., Garbay, C., Baud, R., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIME 1997. Lecture Notes in Computer Science, vol 1211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029465

Download citation

  • DOI: https://doi.org/10.1007/BFb0029465

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62709-8

  • Online ISBN: 978-3-540-68448-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation