Sathyabama Institute of Science and Technology, Chennai, India.
Department of Electronics and Instrumentation, RMD Engineering College, Chennai, India.
J Med Syst. 2019 May 31;43(7):211. doi: 10.1007/s10916-019-1355-9.
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.
肺癌是当今世界所有癌症中导致死亡的主要原因。如果癌症在 1 期就能被诊断出来，患者的存活率为 85%。挖掘患者的记录可以帮助在 1 期诊断癌症。使用多类神经网络有助于在疾病 1 期本身就识别出该疾病。多类神经网络的实现达到了 100%的准确率。使用神经网络方法创建的模型有助于在 1 期识别肺癌，从而提高患者的生存率。该模型可以作为医生的预诊断工具。
