Evaluation of psoriasis skin disease classification using convolutional neural network

• DOI: 10.11591/ijai.v9.i2.pp349-355
• Publication Date: 2020-05-19T23:23:46Z
• Authors: Rosniza Binti Roslan; Iman Najwa Mohd R...; Nurbaity Sabri; Zaidah Ibrahim
• Keywords: Human skin

<span lang="EN-GB">Skin disease has lower impact on mortality compared to others but instead it greater effect quality of life because involves symptoms such as pain, stinging and itchiness. Psoriasis is one the ordinary skin diseases which are relapsing, chronic immune-mediated inflammatory disease. It estimated about 125 million people worldwide being infected with various types infection. </span><span lang="EN-GB">Challenges arise when patients only predict type they had without accurately precisely examined. This human being, observe look at surface their naked eye, where there some limits, for example, vision lacks accuracy, reproducibility quantification in collection image information. As Plaque Guttate most common happened among people, this paper presents an evaluation classification using Convolutional Neural Network. A total 187 images consist 82 105 been used retrieved from Image Library, International Council (IPC) DermNet NZ. Network (CNN) applied extracting features analysing showed promising CNN accuracy rate 82.9% 72.4% disease, respectively.</span>