November 8, 2014
Notes: Gilmore, Stephen J
Australas J Dermatol. 2013 Feb;54(1):1-8. doi: 10.1111/j.1440-0960.2012.00883.x. Epub 2012 Apr 16.
Author Address: Dermatology Research Centre, University of Queensland, School of Medicine, Princess Alexandra Hospital, Brisbane, Australia. firstname.lastname@example.org
Reference Type: Journal Article
Record Number: 4580Author: Giotis, I., Visser, M., Jonkman, M. and Petkov, N.
Title: Discriminative power of visual attributes in dermatology
Journal: Skin Res Technol
Short Title: Discriminative power of visual attributes in dermatology
Alternate Journal: Skin research and technology : official journal of International Society for Bioengineering and the Skin
ISSN: 1600-0846 (Electronic)
Accession Number: 22724513
Keywords: Bayes Theorem
Abstract: BACKGROUND/PURPOSE: Visual characteristics such as color and shape of skin lesions play an important role in the diagnostic process. In this contribution, we quantify the discriminative power of such attributes using an information theoretical approach. METHODS: We estimate the probability of occurrence of each attribute as a function of the skin diseases. We use the distribution of this probability across the studied diseases and its entropy to define the discriminative power of the attribute. The discriminative power has a maximum value for attributes that occur (or do not occur) for only one disease and a minimum value for those which are equally likely to be observed among all diseases. RESULTS: Verrucous surface, red and brown colors, and the presence of more than 10 lesions are among the most informative attributes. A ranking of attributes is also carried out and used together with a naive Bayesian classifier, yielding results that confirm the soundness of the proposed method. CONCLUSION: proposed measure is proven to be a reliable way of assessing the discriminative power of dermatological attributes, and it also helps generate a condensed dermatological lexicon. Therefore, it can be of added value to the manual or computer-aided diagnostic process.