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Use of Support Vector Machines to Predict the Success of Wart Treatment Methods

Uzun, Rukiye | Isler, Yalcini | Toksan, Mualla

Conference Object | 2018 | 2018 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS CONFERENCE (ASYU) , pp.1 - 4

Warts are virus-based dermatosis that are common in the society. In this study, it was predicted if the method to be applied in the treatment of warts will success or not using a machine learning method. For this purpose, two online and freely available datasets of 180 patients with common warts and plantar warts, who are treated with cryotherapy and immunotherapy methods, were used together. As a result, the algoerithm of support vector machines predicted whether the selected treatment success with an accuracy of 85.46%.


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