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

机译:使用支持向量机预测疣治疗方法的成功

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摘要

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%.
机译:疣是在社会中常见的基于病毒的皮肤病。在这项研究中,预测了将使用机器学习方法的疣治疗方法是否成功。为此,将180例经冷冻疗法和免疫疗法治疗的普通疣和plant疣患者的在线和免费数据集一起使用。结果,支持向量机的算法预测出所选治疗是否成功,准确率为85.46%。

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