Title: Survey of various methods for diagnostic signatures for cutaneous melanoma from genetic and imaging data
Authors: K. Thenmozhi; M. Rajesh Babu
R&D Center, Bharathiar University, Coimbatore, India
Department of CSE, Karpagam College of Engineering (Autonomous), Coimbatore, India
Abstract: Early diagnosis of cutaneous melanoma is very hard for experienced dermatologists. Even though a lot of advanced imaging techniques and clinical diagnostic algorithms such as dermoscopy and the ABCD rule of dermoscopy respectively are available. The accuracy is an issue of distress (estimated to be about 75%-85%) especially with oblique pigmented lesions. An effective diagnosis can be achieved by reducing the viewer variability's found in dermatologists' examinations. In order to improve some of existing methods and budding new techniques to ease accurate, fast and reliable diagnosis of cutaneous melanoma. In this paper, different types diagnostic system of melanoma namely, pre-processing feature extraction, feature selection and classification is explained. The results of feature selection were optimised from advanced classes of classification techniques; namely, two weighted k-nearest neighbour (k-NN) classifiers (k = 1, 30), a decision tree (DT), and the random forest (RF) algorithm are employed.
Keywords: classification; composite biomarkers; cutaneous melanoma CM; dermoscopy and feature selection.
Int. J. of Business Intelligence and Data Mining, 2018 Vol.13, No.1/2/3, pp.40 - 51
Available online: 03 Nov 2017