Abstract
In this paper, computer-aided diagnosing and classification of melanoid skin lesions is briefly described. The main goal of our research was to elaborate and to present new version of the developed melanoma diagnosis support system, available on the Internet. It is a subsystem of our complementary melanoma diagnosis and classification web center system. Here, we present functionality, structure and operation of this subsystem. In its current version, five learning models are implemented to provide five independent results of diagnosis. Then, a specific voting algorithm is applied to select the correct class (concept) of the diagnosed skin lesion. Developed tool enables users to make early, non-invasive diagnosing of melanocytic lesions. It is possible using built-in set of instructions that animate diagnosis of four basic lesions types: benign nevus, blue nevus, suspicious nevus and melanoma malignant.
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Paja, W., Wrzesień, M. (2011). Melanoma Diagnosis and Classification Web Center System: The Non-invasive Diagnosis Support Subsystem. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2011. Lecture Notes in Computer Science(), vol 6870. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23184-1_8
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DOI: https://doi.org/10.1007/978-3-642-23184-1_8
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