AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL
LAWRENCE OMOTOSHO 1, KEHINDE SOTONWA 2, BENJAMIN ADEGOKE 3, OLUWASHINA OYENIRAN 4, JOSHUA OYENIYI 1* 1. Department of Information and Communication Technology, Osun State University, Osogbo, Osun State, Nigeria
2. Department of Computer Science and Information Technology, Bells University of Technology, Ota, Ogun State, Nigeria
3. Department of Computer Engineering, Federal Polytechnic, Ile-Oluji, Ondo State, Nigeria
4. Department of Computer Science, Ajayi Crowther University, Oyo, Oyo State, Nigeria
*Corresponding author, email: thejoshoyeniyi@gmail.com
The use of computer technology has significantly advanced the medical sector, and many computer technologies have been used to develop healthcare, such as the patient management system, monitoring and control systems, and diagnostic systems. Technological advances in healthcare have also helped in saving numerous patients and are constantly improving our quality of life. Technology in the medical sector has also had a major effect on almost all healthcare professional techniques and practices. In order to facilitate rapid diagnosis and treatment of different skin diseases by the use of a deep learning model, this study developed a comprehensive framework to improve the decision-making of dermatologists in Nigeria in terms of the diagnosis of selected skin diseases. The developed system achieved the network accuracy of 98.44 % and the validation accuracy of the test set is 99.44 % as specified by the training results, further testing reveal that the developed system yielded rejection rate of 2.2 % and recognition accuracy of 97.8 %.
