Image Recognition System for Diagnosis Support of Melanoma Skin Lesion

Pawe,; Cudek,; Wies,; Paja, Wiesław; Wrzesie, Mariusz

doi:10.1007/978-3-642-25261-7_17

Cited by 2 publications

(1 citation statement)

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“…It is also used in development of diagnosis platforms such as DERMA [4] or IMDLS systems [5]. Previous research [5][6][7][8] focused on using of data mining and image mining techniques to provide early support to diagnosis of melanocytic lesions. Now, it is proposed to apply feature selection methods to find interesting features inside investigated melanocytic datasets.…”

Section: Introductionmentioning

confidence: 99%

Medical diagnosis support and accuracy improvement by application of total scoring from feature selection approach

Paja

2015

Annals of Computer Science and Information Systems

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Abstract-Melanoma is the most deadly form of skin cancer. Early detection and successful treatment of this disease often is possible. The main goal of this paper is to present results of application of feature selection method to find the most important or all important features that characterize melanocytic spots on the skin and in this way defining of a new Total Dermatoscopy Score formula. Thus, it is possible to decrease dimensionality of that problem. Results gathered during research focus on about six from thirteen descriptive attributes which are the most relevant and are stated as core attributes. Based on these attributes a simple total scoring method could be applied to improve prediction (diagnosis) results, additionally also reducing complexity of problem. Results were acquired by application of six different machine learning algorithms and estimated using several evaluation measures.

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