Karlik, BekirHarman, Gunes2020-03-262020-03-262013978-1-4673-4672-6; 978-1-4673-4669-6https://hdl.handle.net/20.500.12395/29332IEEE 33rd International Scientific Conference on Electronics and Nanotechnology (ELNANO) -- APR 16-19, 2013 -- Kyiv, UKRAINEEarly diagnosis and appropriate treatment remain a necessary challenge. Dermatologic emergencies have insufficient attention by the general population and by physicians from other specialties. The differential diagnosis of erythemato-squamous diseases is a real problem in dermatology. They all share the clinical features of erythema and scaling with very little differences. These diseases are psoriasis, seboreic dermatitis, lichen planus, pityriasis rosea, cronic dermatitis, and pityriasis rubra pilaris. Usually a biopsy is necessary for the diagnosis but unfortunately these diseases share many histopathological features as well. In this study, computer-aided software was developed to diagnosis dermatological diseases by using artificial neural networks. The supervised back-propagation algorithm is used to train the networks. Classification of the average value of sensitivity (or recognition percentage) was found as 98% for six erythemato-squamous diseases.eninfo:eu-repo/semantics/closedAccessEarly diagnosisDermatology diseasesSoftwareArtificial neural networksConference Object276279N/AWOS:000325186800064N/A