Abstract
Dermatology is one of the fields where computer aided diagnostic is developing rapidly. The presented research concentrates on creation of automatic methods for melanoid skin lesions diagnosis using machine learning methods. In the experiments 1010 samples described in [5] are used. There are 275 melanoma cases and 735 benign ones. Three different machine learning methods are applied, namely the Naive Bayes classifier, the Random Forest, the K* instance-based classifier, and Attributional Calculus. The obtained results confirm that clinical history context and dermoscopic structures together with the selected machine learning methods may be an important and accurate diagnostic tool.
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Grzesiak-Kopeć, K., Nowak, L., Ogorzałek, M. (2015). Automatic Diagnosis of Melanoid Skin Lesions Using Machine Learning Methods. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_51
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DOI: https://doi.org/10.1007/978-3-319-19324-3_51
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