International Journal of Academic and Applied Research (IJAAR)   Year: 2021 | Volume: 5 | Issue: 4 | Page No.: 47-55 ANN for the Classification of Eryhemato-Squamous Disease Baraa Iyad Al-Kahlout, Musab Maher Naeem, Mohammed Jihad Shepherd Abstract: Classification of Erythmato-Squamous Diseases (ESD) is a major challenge in the field of dermatology. The ESD diseases are classified into six categories. The aim of this paper is to use the Artificial Neural Network to classify the six classes of ESD with high accuracy. We used the JustNN tool which a backpropagation feed forward methodology for the classification of ESD for modeling. For this purpose, the dermatology dataset was collected from UCI machine learning repository. In order to evaluate the proposed model we trained and validated it using the pre-process dataset. The proposed model achieved an accuracy of 98.36%. Results indicated that the proposed classifier is useful.