A Novel Approach for Lung Cancer Detection Using Deep Learning Algorithms

Authors

  • Shashikala S. Assistant Professor, Department of Computer Science, New Horizon College. Bengaluru
  • Nargis Parveen Lecturer, Department of Computer Science, Faculty of Computing and Information Technology, Northern Border University, Kingdom of Saudi Arabia
  • Albia Maqbool Lecturer, Department of Computer Sciences Faculty of Computing and Information Technology, Northern Border University, Rafha, Kingdom of Saudi Arabia
  • Humera Khan Assistant Professor, Department of Information Systems, Faculty of Computing and Information Technology, Northern Border University, Kingdom of Saudi Arabia
  • Sana Khamis Alghadeer Lecturer Northern Border University College of Science
  • Gurwinder Singh Associate Professor, Department of AIT-CSE, Chandigarh University, Punjab, India

Keywords:

Lung cancer, Deep learning, Medical imaging, CNN

Abstract

Lung cancer is a pervasive and life-threatening disease, often identified at progressive phases, which significantly reduces treatment achievement rates. Early and accurate discovery of lung cancer is paramount for refining patient results. In this research, we present a comprehensive study on the application of deep learning techniques for lung cancer detection. Leveraging a diverse dataset of medical images, we developed and fine-tuned deep convolutional neural networks (CNNs) to identify lung cancer lesions with high sensitivity and specificity. Our results showcase the potential of deep learning as a valuable tool for early lung cancer detection, with the promise of aiding clinicians in timely diagnosis and intervention. We discuss the methodology, experimental results, and the implications of our findings, emphasizing the significant impact on the field of medical imaging and cancer diagnostics.

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References

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Published

07.02.2024

How to Cite

S., S. ., Parveen, N. ., Maqbool, A. ., Khan, H. ., Alghadeer, S. K. ., & Singh, G. . (2024). A Novel Approach for Lung Cancer Detection Using Deep Learning Algorithms. International Journal of Intelligent Systems and Applications in Engineering, 12(15s), 471–480. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4771

Issue

Vol. 12 No. 15s (2024)

Section

Research Article

License

Copyright (c) 2024 Shashikala S., Nargis Parveen, Albia Maqbool, Humera Khan, Sana Khamis Alghadeer, Gurwinder Singh

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