Abstract
Case-based classifiers try to solve given cases using the solutions of the most similar cases. In several medical domains, sometimes they do not perform well because of their reliability. In this paper we build a Case-Based Classifier in order to diagnose mammographic images. We explain different methods and behaviours that have been added to a Case-Based Classifier in order to improve its reliability and make it suitable for this complex domain where an error may be fatal.
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Vallespí, C., Golobardes, E., Martí, J. (2002). Improving Reliability in Classification of Microcalcifications in Digital Mammograms Using Case-Based Reasoning. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds) Topics in Artificial Intelligence. CCIA 2002. Lecture Notes in Computer Science(), vol 2504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36079-4_9
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DOI: https://doi.org/10.1007/3-540-36079-4_9
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