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Lung Cancer Prediction using Machine Learning: A Comprehensive Approach

机译:基于机器学习的肺癌预测:一种综合方法

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The prominent cause of cancer-related mortality throughout the globe is “Lung Cancer”. Hence beforehand detection, prediction and diagnosis of lung cancer has become essential as it expedites and simplifies the consequent clinical board. To erect the progress and medication of cancerous conditions machine learning techniques have been utilized because of its accurate outcomes. Various types of machine learning algorithms(ML) like Naive Bayes, Support Vector Machine (SVM), Logistic regression, Artificial Neural Network (ANN), have been applied in the healthcare sector for analysis and prognosis of lung cancer. In this review, factors that cause lung cancer and application of ML algorithms are discussed up to date and also draws special attention to their relative strengths and weaknesses. This paper will help the researchers to quickly go through the related literature instead of referring to the many papers.□
机译:在全球范围内,与癌症有关的死亡率的主要原因是“肺癌”。因此,肺癌的预先检测,预测和诊断已变得必不可少,因为它可以加快并简化随后的临床程序。由于其准确的结果,为了提高癌症状况的进展和药物治疗,已经使用了机器学习技术。各种类型的机器学习算法(ML),如朴素贝叶斯(Naive Bayes),支持向量机(SVM),逻辑回归,人工神经网络(ANN),已在医疗保健领域中用于肺癌的分析和预后。在这篇综述中,引起肺癌的因素和ML算法的应用得到了最新的讨论,并特别关注了它们的相对优势和劣势。本文将帮助研究人员快速浏览相关文献,而不必参考大量论文。□

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