A support vector machine for decision support in melanoma recognition

Experimental Dermatology
Stephen GilmoreH Peter Soyer

Abstract

The early diagnosis of melanoma is critical to achieving reduced mortality and increased survival. Although clinical examination is currently the method of choice for melanocytic lesion assessment, difficulties may arise in the diagnosis of atypical lesions. From both the naked eye and dermoscopic perspective, dysplastic naevi often exhibit a prominent heterogeneity of structure that renders their clinical distinction from melanoma difficult. To address these problems in diagnosis, there exists a heightened interest among researchers regarding the utility of machine learning techniques in computerised image analysis. Here we report on the utility, for dermatologists, of support vector machine (SVM) technology in melanoma diagnosis, using an archive of 199 digital dermoscopic images of excised atypical melanocytic lesions. Our best validation models achieved an average sensitivity and specificity for melanoma diagnosis of 0.86 and 0.72, respectively. Applying the best model to our test set yielded a sensitivity of 0.89, a diagnostic odds ratio of 14.09 and an area under the receiver operated characteristic curve (AUC) of 0.76. Advantages of the procedure implemented are the simplicity of feature extraction and the computationall...Continue Reading

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Citations

Feb 28, 2014·International Journal of Biomedical Imaging·Ammara Masood, Adel Ali Al-Jumaily
Oct 16, 2012·Artificial Intelligence in Medicine·Konstantin Korotkov, Rafael Garcia
Jul 24, 2012·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Mutlu Mete, Nikolay Metodiev Sirakov
Mar 10, 2015·Computational and Structural Biotechnology Journal·Konstantina KourouDimitrios I Fotiadis
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May 10, 2016·Journal of Dermatological Science·P RubegniG Cevenini
Jan 24, 2015·PloS One·Samuel C HamesTarl W Prow
Nov 19, 2011·Dermatology : International Journal for Clinical and Investigative Dermatology·Z BoyceH P Soyer
Sep 8, 2018·PloS One·Stephen J Gilmore
Dec 7, 2018·The Cochrane Database of Systematic Reviews·Jacqueline DinnesUNKNOWN Cochrane Skin Cancer Diagnostic Test Accuracy Group
Dec 7, 2018·The Cochrane Database of Systematic Reviews·Lavinia Ferrante di RuffanoUNKNOWN Cochrane Skin Cancer Diagnostic Test Accuracy Group
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Feb 7, 2019·PloS One·Grzegorz Surówka, Maciej Ogorzalek
Jun 20, 2019·JAMA Dermatology·Vincent DickPhilipp Tschandl
May 5, 2011·Experimental Dermatology·Peter AbergStig Ollmar
Nov 1, 2020·Medical Image Analysis·Eduardo PérezSebastián Ventura
Jan 24, 2020·Journal of the American Academy of Dermatology·George A ZakhemRoger S Ho

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