Analysis of Different Classification Algorithms for Lung Cancer Detection

Authors

  • Mrs. J. Sarada  Assistant Professor, Department of Computer Applications, Chadalawada Ramanamma Engineering College (Autonomous), Tirupati, Andhra Pradesh, India
  • K R Bindupriya  PG Scholar, Department of Computer Applications, Chadalawada Ramanamma Engineering College (Autonomous), Tirupati, Andhra Pradesh, India

Keywords:

C Lung CT Scan images. Deep Learning, CNN, Transfer Learning, RF, SVM, and DT.

Abstract

Early diagnosis of lung cancer is crucial to ensure curative treatment and increase survival rates. Lung CT Scan imaging is the most frequently used method for diagnosing Cancer. However, the examination of Lung CT Scans is a challenging task and is prone to subjective variability. In this study, we developed a computer-aided diagnosis system for automatic Lung Cancer detection using Lung CT Scan images. We employed deep transfer learning to handle the scarcity of available data and designed a Convolutional Neural Network (CNN) model along with the Machine learning methods: Random Forest (RF), Support Vector Machines (SVM), and Decision Tree (DT). The proposed approach was evaluated on publicly available Covid-19 CT scan dataset.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-10-30

Issue

Volume 8, Issue 5, September-October-2022

Section

Research Articles

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How to Cite

[1]
Mrs. J. Sarada, K R Bindupriya, " Analysis of Different Classification Algorithms for Lung Cancer Detection" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.190-200, September-October-2022.