Discriminative power of visual attributes in dermatology.
OBJECTIVE
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.


CONCLUSIONS
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.
Johann Bernoulli Institute for Mathematics and Computing Science, University of Groningen, Groningen, The Netherlands. i.e.giotis@rug.nl
Ioannis
I
Giotis
Margaretha
M
Visser
Marcel
M
Jonkman
Nicolai
N
Petkov
D001499:Bayes Theorem; D003116:Color; D016208:Databases, Factual; D003880:Dermatology / Q000379:methods* / Q000592:standards; D003936:Diagnosis, Computer-Assisted / Q000379:methods* / Q000592:standards; D019277:Entropy; D006801:Humans; D007257:Information Theory; D008954:Models, Biological; D012867:Skin / Q000473:pathology; D012871:Skin Diseases / Q000145:classification / Q000473:pathology*