用反向传播神经网络检测乳腺癌,并对不同神经元进行比较

P. Pawar, D. Patil
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引用次数: 4

摘要

乳腺癌是乳腺细胞不受控制的生长。人体内的细胞每天都在分裂、生长和死亡。细胞的这种分裂和生长在大多数情况下是有序的,但当它们的生长失去控制时。细胞不受控制的生长形成肿块,称为肿瘤。一种肿瘤,一般分为良性(无害)和恶性(对健康有害)两种类型。发生在乳房的恶性肿瘤称为乳腺癌。本文采用反向传播神经网络对不同神经元模型的乳腺癌进行分类。它可以帮助医生做出正确的决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Breast cancer detection using backpropagation neural network with comparison between different neuron
Breast cancer is an uncontrolled growth of breast cells. Cell in the body get divide, grow and die every day. This division and growth of cell is most of the in orderly manner but when their growth is out of control. The uncontrolled growth of cell forms the lump which is called as tumor. A tumor generally of two types benign (not dangerous) or malignant (dangerous to health). The malignant tumor which develops in breast is called as breast cancer. In this paper we use backpropagation neural network for classification of breast cancer with different neuron models. It can assist doctors for taking correct decisions.
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