Authors : Mazniha Berahim, Noor Azah Samsudin and Shelena Soosay Nathan
Abstract: The result of medical images diagnostic will affect clinical decision-making for diagnostics as well as the treatment planning. Thus, an accurate classifier is needed to improve automated diagnostic result. Each design of classifier and all phases involved will lead to better classification result for the accurate diagnostic. Many techniques have been used either conventional, modification or extension. However, limited review has been done in listing the recent supervised techniques in parametric and non-parametric categories for medical diagnostic procedure. Thus, the aim of this study is to provide an overview of medical image diagnostic using supervised technique and the factors to be considered for developing an accurate classifier. This will inspire newbie researcher or radiologist for and to be used when analyzing different types of medical image. The current studies of image classification task were summarized, the prominent parametric and non-parametric supervised technique identified and discussed in this study.
Mazniha Berahim, Noor Azah Samsudin and Shelena Soosay Nathan, 2018. A Review: Supervised Technique for Automated Disease Diagnostic Using Medical Image. Journal of Engineering and Applied Sciences, 13: 3152-3158.