不同机器学习方法识别肺癌的综合分析

G. Paliwal, U. Kurmi
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引用次数: 4

摘要

现在每天肺部都是非常重要的身体部位,因为癌症问题难治难愈。肺癌是人类生命中危害最大的疾病。有很多患者,现在远离癌症有多安全,每天也会遭受与covid相关的问题。在这篇调查论文中讨论了不同的机器学习方法来治疗肺癌。用于肺癌的检测。首先使用机器学习,我们收集训练数据集用于测试数据集,借助数据集的训练,我们必须学习系统学习机器来治疗肺癌。本文讨论了利用医学图像处理(MIP)技术进行癌症检测的不同机器学习方法。图像处理有助于癌症检测和机器学习技术预测细胞起源。深度神经网络是检测此类疾病的有力工具。在综述中讨论了不同的技术及其规范。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comprehensive Analysis of Identifying Lung Cancer via Different Machine Learning Approach
Now a day’s lungs are very important body part due to indomitable cancer problem rice in patient. Lung cancer is the most harmful disease in human life. There are many patients, how safer from cancer now a day’s also suffer from covid related problems. In this survey paper discuss the different machine learning approach to disease lung cancer. for the detection of lung cancer. using machine learning first we collection the training data set for testing data set with the help of training of data set we have to learn system learn machine to disease the lung cancer. In this article discuss different machine learning approach for cancer detection using medical image processing (MIP) techniques. Image proceeding’s help to detection the cancer and machine learning technique prediction cell origination. Deep neural network is powerful tool for detection such type of deceases detection. In the review discuss the different techniques and it’s specification.
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