Abstract
This paper presents the application of a method for mining data in a multi-relational database that contains some information about patients strucked down by chronic hepatitis. Our approach may be used on any kind of multirelational database and aims at extracting probabilistic tree patterns from a database using Grammatical Inference techniques. We propose to use a representation of the database by trees in order to extract these patterns. Trees provide a natural way to represent structured information taking into account the statistical distribution of the data. In this work we try to show how they can be useful for interpreting knowledge in the medical domain.
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Habrard, A., Bernard, M., Jacquenet, F. (2003). Multi-relational Data Mining in Medical Databases. 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_50
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DOI: https://doi.org/10.1007/978-3-540-39907-0_50
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