基于特征选择和CNN的乳腺癌肿瘤分类

S. Anparasy
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引用次数: 0

摘要

乳腺癌是世界上最危险的疾病之一,每年有近200万新病例被诊断出来。它从乳房组织开始,然后扩散到身体的其他部位。乳腺癌的早期发现对于挽救女性的生命非常重要,因为它与可用治疗选择的数量增加有关。良性和恶性是肿瘤的主要类型,它们分别是癌性和非癌性。良性肿瘤并不危险,因为它不会破坏附近的组织,也不会扩散或生长。恶性肿瘤侵入邻近组织、血管,并通过转移扩散到身体其他部位。因此,鉴别乳腺癌的良恶性有助于早期发现乳腺癌。目前,使用机器学习技术对肿瘤类型进行分类,从而提高了提升质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Breast cancer tumors using Feature Selection and CNN
Breast cancer is one of the most dangerous diseases in the world and almost two million new cases are diagnosed every year. It starts from the breasts tissue and then spreads to other parts of the body. Early detection of breast cancer is important to save the life of a woman as it is related with a risen number of available treatment options. Benign and malignant are the major types of tumors and they are cancerous and non-cancerous, respectively. Benign is not dangerous since it does not destroy the nearby tissues and cannot spread or grow. Malignant tumor invades neighbouring tissues, blood vessels and spreads to other parts of the body by metastasis. Therefore, differentiating malignant from benign will help to detect breast cancer in its early stage. Nowadays, machine learning techniques are used to classify the tumor types hence the quality of lift is increased.
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