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Multi-Class Neural Networks to Predict Lung Cancer

机译:多级神经网络预测肺癌

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摘要

Lung Cancer is the leading cause of death among all the cancers' in today's world. The survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of the patient records can help in diagnosing cancer during Stage 1. Using a multi-class neural networks helps to identify the disease during its stage 1 itself. The implementation of multi-class neural networks has yielded an accuracy of 100%. The model created using the neural networks approach helps to identify lung cancer during Stage 1 itself, thus the survival rate of the patients can be increased. This model can serve as pre-diagnosis tool for the practitioners.
机译:肺癌是当今世界中所有癌症中死亡的主要原因。 如果患者在阶段可以诊断患者的患者的存活率为85%。患者记录的开采可以有助于在阶段1期间诊断癌症1.使用多级神经网络有助于在其第1阶段识别疾病 。 多级神经网络的实现产生了100%的精度。 使用神经网络创建的模型有助于在第1阶段本身鉴定肺癌,因此患者的存活率可以增加。 该模型可以作为从业者的预诊断工具。

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