Abstract
The goal of the TeCoMed project is to compute early warnings against forthcoming waves or even epidemics of infectious diseases, especially of influenza, and to send them to interested practitioners, pharmacists etc. in the German federal state of Mecklenburg-Western Pomerania. Usually, each winter one influenza wave can be observed in Germany. In some years they are nearly unnoticeable, while in other years doctors and pharmacists even run out of vaccine. Because of the irregular cyclic behaviour it is insufficient to determine average values based on former years and to give warnings as soon as such values are noticeably overstepped. So, we have developed a method that combines Temporal Abstraction with Case-based Reasoning. The idea is to search for former, similar cases and to make use of them for the decision whether early warning is appropriate or not.
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References
Nichol, K.L. et al.: The effectiveness of Vaccination against Influenza in Adults. New England Journal of Medicine 333 (1995) 889–893
Hwang, M.Y.: Do you have the flu? JAMA 281 (1999) 962
Dowdle, W.R.: Informed ConsentNelson-Hall Inc. Chicago, III
Prou, M., Long, A., Wilson, M., Jacquez, G., Wackernagel, H., Carrat, F.: Exploratory Temporal-Spatial Analysis of Influenza Epidemics in France. In: Flahault, A., Viboud, C., Toubiana, L., Valleron, A.-J.: Abstracts of the 3rd International Workshop on Geography and Medicine, Paris, October 17–19 (2001) 17
Shindo, N. et al.: Distribution of the Influenza Warning Map by Internet. In: Flahault, A., Viboud, C., Toubiana, L., Valleron, A.-J.: Abstracts of the 3rd International Workshop on Geography and Medicine, Paris, October 17–19 (2001) 16
Farrington, C.P., Beale, A.D.: The Detection of Outbreaks of Infectious Disease. In Gierl, L., Cliff, A.D., Valleron, A.-J., Farrington, P., Bull, M. (eds.): GEOMED’ 97, International Workshop on Geomedical Systems, Teubner-Verlag, Stuttgart Leipzig (1997)97–117
Shahar, Y.: A Framework for Knowledge-Based Temporal Abstraction. Artificial Intelligence 90 (1997) 79–133
Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.): Case-Based Reasoning Technology, Lecture Notes in Artificial Intelligence, Vol. 1400. Springer-Verlag, Berlin Heidelberg New York (1998)
Perner, P.: Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin? In: Perner, P. (eds.): Machine Learning and Data Mining in Pattern Recognition, Lecture Notes in Artificial Intelligence, Vol. 2123. Springer-Verlag, Berlin Heidelberg New York (2001) 35–51
Viboud, C., Boelle, P.-Y., Carrat, F., Valleron, A.-J., Flahault, A.: Forecasting the spatio-temporal spread of influenza epidemics by the method of analogues. In: Abstracts of the 22nd Annual Conference of the International Society of Clinical Biostatistics, Stockholm, August 20–24 (2001) 71
Lorenz, E.N.: Atmospheric predictability as revealed by naturally occuring analogies. J Atmos Sci (1969) 26
Schmidt, R., Gierl, L.: Temporal Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications. In: Perner, P. (eds.): Machine Learning and Data Mining in Pattern Recognition, Lecture Notes in Artificial Intelligence, Vol. 2123. Springer-Verlag, Berlin Heidelberg New York (2001) 23–34
Schmidt, R., Pollwein, B., Gierl, L.: Medical multiparametric time course prognoses applied to kidney function assessments. Int J of Medical Informatics 53 (2–3) (1999) 253–264
Aamodt, A., Plaza, E.: Case-based reasoning: Foundation issues. Methodological variation-and system approaches. AI Comunications 7(1) (1994)39–59
Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann Publishers, San Mateo (1993)
Macura, R., Macura, K.: MacRad: Radiology image resources with a case-based retrieval system. In: Aamodt, A., Veloso, M. (eds.): Case-Based Reasoning Research and Development, Proceedings of ICCBR-95, Lecture Notes in Artificial Intelligence, Vol. 1010. Springer-Verlag, Berlin Heidelberg New York (1995) 43–54
Larizza, C., Bellazzi, R., Riva, A.: Temporal abstraction for diabetic patients management. In: Keravnou, E., Garbay, C., Baud, R., Wyatt, J. (eds.): Proceedings of the 6th Conference on Artificial Intelligence in Medicine (AIME-97), Lecture Notes in Artificial Intelligence, Vol. 1211. Springer-Verlag, Berlin Heidelberg New York (1997) 319–330
Miksch, S., Horn, W., Popow, C., Paky, F.: Therapy planning using qualitative trend descriptions. In: Barahona, P., Stefanelli, M., Wyatt, J. (eds.): Proceedings of the 5th Conference on Artificial Intelligence in Medicine (AIME-95), Lecture Notes in Artificial Intelligence, Vol. 934. Springer-Verlag, Berlin Heidelberg New York (1995) 197–208
Wilke, W., Smyth, B., Cunningham, P.: Using Configuration Techniques for Adaptation. In: Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.): Case-Based Reasoning Technology, Lecture Notes in Artificial Intelligence, Vol. 1400. Springer-Verlag, Berlin Heidelberg New York (1998) [8] 139–168
Carrat, F., Flahault, A., Boussard, E., Farron, N., Dangoumau, L., Valleron, A.-J.: Surveillance of influenza-like illness in France: The example of the 1995-96 epidemic. Journal of Epidemiology Community Health 52 (Suppl1) (1998) 32–38
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Schmidt, R., Gierl, L. (2002). Case-Based Reasoning for Prognosis of Threatening Influenza Waves. In: Perner, P. (eds) Advances in Data Mining. Lecture Notes in Computer Science(), vol 2394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46131-0_6
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DOI: https://doi.org/10.1007/3-540-46131-0_6
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