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首页> 外文期刊>International journal of biomedical engineering and technology >Hybrid computing based intelligent system for breast cancer diagnosis
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Hybrid computing based intelligent system for breast cancer diagnosis

机译:基于混合计算的乳腺癌智能诊断系统

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Breast cancer is one of the major causes of death in women which accounts one out of eight. As primary cause is still unknown, early detection increases better treatment and improves total recovery. We present some novel hybrid approaches for classification of breast cancer. Artificial Neural Network (ANN) which suffers credit assignment problem can be avoided by modular and evolutionary artificial neural network which achieves simple and small individual neural network. Ensemble of ANN is to obtain a more reliable and accurate ANN. Evolutionary Neural Network (ENN) is used for optimization of neural network learning and design. The best accuracies achieved for diagnosis are around 99% using breast cancer datasets.
机译:乳腺癌是女性死亡的主要原因之一,占八分之一。由于主要病因仍未知,因此及早发现可提高治疗效果并改善总恢复率。我们提出了一些新型的乳腺癌混合分类方法。可以通过模块化和进化的人工神经网络来避免遭受信用分配问题的人工神经网络(ANN),该神经网络可以实现简单而又小的个体神经网络。人工神经网络的集成是为了获得更可靠,更准确的人工神经网络。进化神经网络(ENN)用于优化神经网络的学习和设计。使用乳腺癌数据集可实现的最佳诊断准确性约为99%。

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