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Normalized Neural Networks for Breast Cancer Classification

机译:乳腺癌分类的标准化神经网络

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In almost all parts of the world, breast cancer is one of the major causes of death among women. But at the same time, it is one of the most curable cancers if it is diagnosed at early stage. This paper tries to find a model that diagnose and classify breast cancer with high accuracy and help to both patients and doctors in the future. Here we develop a model using Normalized Multi Layer Perceptron Neural Network to classify breast cancer with high accuracy. The results achieved is very good (accuracy is 99.27%). It is very promising result compared to previous researches where Artificial Neural Networks were used. As benchmark test, Breast Cancer Wisconsin (Original) was used.
机译:在几乎所有地区,乳腺癌是女性死亡的主要原因之一。但同时,如果它在早期阶段被诊断出来,它是最可治愈的癌症之一。本文试图找到一种诊断和分类乳腺癌的型号,以高精度,并帮助未来患者和医生。在这里,我们使用归一化的多层Perceptron神经网络开发模型,以高精度对乳腺癌进行分类。实现的结果非常好(精度为99.27%)。与以前使用人工神经网络的研究相比,这是非常有前途的结果。作为基准测试,使用了乳腺癌威斯康辛(原始)。

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