2021
DOI: 10.48161/qaj.v1n2a58
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Lung cancer Prediction and Classification based on Correlation Selection method Using Machine Learning Techniques

Abstract: Lung cancer is one of the leading causes of mortality in every country, affecting both men and women. Lung cancer has a low prognosis, resulting in a high death rate. The computing sector is fully automating it, and the medical industry is also automating itself with the aid of image recognition and data analytics. This paper endeavors to inspect accuracy ratio of three classifiers which is Support Vector Machine (SVM), K-Nearest Neighbor (KNN)and, Convolutional Neural Network (CNN) that classify lung cancer i… Show more

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Cited by 49 publications
(17 citation statements)
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“…Early detection of lung cancer has been addressed by Abdullah et al, 21 who investigate and identify the most effective classifier among SVM, KNN and CNN for early detection, ultimately aiming to contribute to the improvement of prognosis and outcomes for patients with lung cancer. The proposed solution involves applying SVM, KNN and CNN to datasets obtained from the UCI ML repository, which contain information about patients affected by lung cancer.…”
Section: Related Workmentioning
confidence: 99%
“…Early detection of lung cancer has been addressed by Abdullah et al, 21 who investigate and identify the most effective classifier among SVM, KNN and CNN for early detection, ultimately aiming to contribute to the improvement of prognosis and outcomes for patients with lung cancer. The proposed solution involves applying SVM, KNN and CNN to datasets obtained from the UCI ML repository, which contain information about patients affected by lung cancer.…”
Section: Related Workmentioning
confidence: 99%
“…CNN is often used to solve various pattern and image recognition problems. Deep learning approaches are effective and suitable for visuals [12]. The CNN model is a combination of the following types: convolutional layers, pooling layers, fully connected layers, and fully connected layers that extract features from the input, minimize the size for computational performance and classify an image respectively [10].…”
Section: Augmentation Architectures Of Convolution Neural Network (Cnn)mentioning
confidence: 99%
“…Ranker search method used with CA. Features are prioritized and those that are most suited for use in the machine learning method are filtered based on their Correlation values [38,43]. By the combination of this Correlation attribute evaluator with the Ranking method of Search is applied to the Leukemia dataset.…”
Section: Fig 3 Leukemia Diagnosis Proposed Model Flowchart Diagrammentioning
confidence: 99%