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DETECTION OF MALIGNANT MELANOMA WITH SUPERVISED LEARNING: A REVIEW

机译:监督学习下恶性黑素瘤的检测

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Malignant melanoma is increasing in some countries especially in Australia. Computational systems have been proposed for automatic diagnosis of skin cancer in order to aid dermatologist in early assessment of such disease. Several ways for image analysis targeted on dermoscopy imagery are projected for CAD system. To assist dermatologists in their diagnosis is the main aim of such system at an effective automated diagnosis. Malignant Melanoma needs to be diagnosed at their early stage, when the patient has a higher probability of cure. Malignant melanoma is a kind of skin cancer whose severity even leads to death. For decreasing the chances of death earlier detection of Melanoma is necessary and the clinicians can treat the patients to increase the chances of survival. For detection of Melanoma using its features there are some machine learning algorithms are developed. This paper presents the review of Malignant Melanoma with supervised learning.
机译:在某些国家,特别是在澳大利亚,恶性黑色素瘤正在增加。已经提出了用于皮肤癌自动诊断的计算系统,以帮助皮肤科医生对这种疾病进行早期评估。针对CAD系统计划了几种针对皮肤镜图像的图像分析方法。协助皮肤科医生进行诊断是这种系统进行有效自动诊断的主要目的。当患者治愈的可能性更高时,需要在早期诊断出恶性黑色素瘤。恶性黑色素瘤是一种皮肤癌,其严重程度甚至会导致死亡。为了减少死亡的机会,必须及早发现黑素瘤,临床医生可以治疗患者以增加生存机会。为了利用其特征检测黑色素瘤,开发了一些机器学习算法。本文介绍了监督学习下的恶性黑色素瘤。

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