Abstract
Few years ago, we have developed an early warning system concerning multiparametric kidney function courses. As methods we applied Temporal Abstraction and Case-based Reasoning. In our current project we apply very similar ideas. The goal of the TeCoMed project is to compute early warnings against forthcoming waves or even epidemics of infectious diseases in the German federal state of Mecklenburg-Western Pomerania. Furthermore, these warnings shall be sent to interested practitioners, pharmacists etc. We have developed a prognostic model for diseases that are characterised by cyclic, but irregular behaviour. So far, we have applied this model to influenza and bronchitis.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Schmidt, R., Pollwein, B., Gierl, L.: Medical Multiparametric Time Course Prognoses Applied to Kidney Function Assessments. Int. J. Med. Inform. 53(2-3), 253–264 (1999)
Schmidt, R., Gierl, L.: Case_based Reasoning for Prognosis of Threatening Influenza Waves. In: Perner, P. (ed.) Advances in Data Mining. LNCS (LNAI), vol. 2394, pp. 99–107. Springer, Heidelberg (2002)
Shahar, Y.: A Framework for Knowledge-Based Temporal Abstraction. Artificial Intelligence 90, 79–133 (1997)
Aamodt, A., Plaza, E.: Case-Based Reasoning: foundation issues. Methodological variation- and system approaches. AI Communications 7(1), 39–59 (1994)
Nichol, K.L., et al.: The effectiveness of Vaccination against Influenza in Adults. New England Journal of Medicine 333, 889–893 (1995)
Dowdle, W.R.: Informed Consent Nelson-Hall, Inc. Chicago, III
Prou, M., et al.: Exploratory Temporal-Spatial Analysis of Influenza Epidemics in France. In: Flahault, A., et al. (eds.) Abstracts of 3rd International Workshop on Geography and Medicine, Paris, p. 17 (2001)
Shindo, N., et al.: Distribution of the Influenza Warning Map by Internet. In: Flahault, A., et al. (eds.) Abstracts of 3rd International Workshop on Geography and Medicine, Paris, p. 16 (2001)
Farrington, C.P., Beale, A.D.: The Detection of Outbreaks of Infectious Disease. In: Gierl, L., et al. (eds.) GEOMED 1997, International Workshop on Geomedical Systems, Teubner Stuttgart, pp. 97–117 (1997)
Viboud, C., et al.: Forecasting the spatio-temporal spread of influenza epidemics by the method of analogues. In: Abstracts of 22nd Annual Conference of the International Society of Clinical Biostatistics, Stockholm, August 20-24, p. 71 (2001)
Lorenz, E.N.: Atmospheric predictability as revealed by naturally occuring analogies. J. Atmos. Sci. p. 26 (1969)
Wilke, W., Smyth, B., Cunningham, P.: Using Configuration Techniques for Adaptation. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.) Case-Based Reasoning Technology. LNCS (LNAI), vol. 1400, pp. 139–168. Springer, Heidelberg (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Schmidt, R., Gierl, L. (2003). Prognosis of Approaching Infectious Diseases. In: Dojat, M., Keravnou, E.T., Barahona, P. (eds) Artificial Intelligence in Medicine. AIME 2003. Lecture Notes in Computer Science(), vol 2780. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39907-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-39907-0_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20129-8
Online ISBN: 978-3-540-39907-0
eBook Packages: Springer Book Archive