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Dermatological disease detection using image processing and machine learning

机译：使用图像处理和机器学习的皮肤病检测

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摘要

Dermatological diseases are the most prevalent diseases worldwide. Despite being common, its diagnosis is extremely difficult and requires extensive experience in the domain. In this research paper, we provide an approach to detect various kinds of these diseases. We use a dual stage approach which effectively combines Computer Vision and Machine Learning on clinically evaluated histopathological attributes to accurately identify the disease. In the first stage, the image of the skin disease is subject to various kinds of pre-processing techniques followed by feature extraction. The second stage involves the use of Machine learning algorithms to identify diseases based on the histopathological attributes observed on analysing of the skin. Upon training and testing for the six diseases, the system produced an accuracy of up to 95 percent.
机译：皮肤病是全世界最普遍的疾病。尽管是常见的，但其诊断非常困难，并且需要在域名的广泛体验。在本研究论文中，我们提供了一种检测各种这些疾病的方法。我们使用双阶段方法，有效地将计算机视觉和机器学习结合在临床评估的组织病理属性，以准确识别疾病。在第一阶段，皮肤病的图像受到各种预处理技术，然后进行特征提取。第二阶段涉及使用机器学习算法基于在分析皮肤分析上观察到的组织病理学属性来识别疾病。在培训和测试六种疾病后，该系统的精度高达95％。

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