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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 12, 2022.
Abstract: Skin diseases are a group of diseases affecting people of all ages, commonly caused by fungi, bacteria, parasites, viruses, and infections. The disease's main symptoms are usually itching all over the skin. Many patients are often underestimated and embarrassed to consult directly with doctors, which in the end, ignores the symptoms of skin diseases. Since they usually have imprecision symptoms, examining skin diseases is complex and challenging. Recently, many efforts have been made to utilize artificial intelligence approaches for diagnosing various diseases based on the patient's condition. This paper aims to develop a novel fuzzy-based medical expert system based on unprecise existing symptoms. The system uses the specialist Doctor's knowledge (dermatologist) to diagnose and provide the patient's severity level for the disease. We have done numerical experiments using 100 (one hundred) test problems to evaluate the performance of the developed system by comparing the result with the recommendations of doctors (dermatologists). It shows that this system succeeds in all tests with an accuracy value of 95.6%. Thus, this system is very beneficial to support doctors in the assessment of skin diseases.
Admi Syarif, Mayda B Fauzi, Aristoteles and Agus Wantoro, “Implementation of Fuzzy Expert System on Skin Diseases” International Journal of Advanced Computer Science and Applications(IJACSA), 13(12), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131264
@article{Syarif2022,
title = {Implementation of Fuzzy Expert System on Skin Diseases},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131264},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131264},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {12},
author = {Admi Syarif and Mayda B Fauzi and Aristoteles and Agus Wantoro}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.