ISSN2320-2882
Impact Factor9.17
UGC ParametersAligned
Low Cost₹1501 / $59
CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Lung Cancer Classification and Prediction with CNN Deep Learning Technique
Authors
Asheesh Mishra , Dr. Devendra Singh Rathore , Dr. Vivek Richhariya
Keywords
Lung Cancer, CNN, Deep Learning, CT- Scan, Classification, Prediction
Abstract
Lung cancer is one of the most life-threatening diseases worldwide, where early detection plays a crucial role in improving survival rates. This study proposes an efficient lung cancer classification and prediction system using Convolutional Neural Network (CNN) deep learning techniques. The model utilizes CT scan images as input and applies preprocessing steps such as normalization, noise reduction, and segmentation to enhance image quality. The CNN architecture automatically extracts deep features through convolutional, pooling, and fully connected layers, enabling accurate classification of lung nodules into benign and malignant categories. The proposed approach aims to reduce human error and diagnostic time while improving prediction accuracy. Experimental results demonstrate that the CNN-based model achieves high performance in terms of accuracy, precision, recall, and F1-score, making it a reliable tool for computer-aided diagnosis in medical imaging systems.
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IJCRT — journal style
"Lung Cancer Classification and Prediction with CNN Deep Learning Technique", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 4, page no.e759-e769, April 2026, Available :https://ijcrt.org/papers/IJCRT2604561.pdf
APA — 7th edition
Mishra, A., Rathore, D. S., & Richhariya, V. (2026). Lung Cancer Classification and Prediction with CNN Deep Learning Technique. International Journal of Creative Research Thoughts, 14(4), e759-e769. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561
MLA — 9th edition
Mishra, Asheesh, et al. "Lung Cancer Classification and Prediction with CNN Deep Learning Technique." International Journal of Creative Research Thoughts, vol. 14, no. 4, 2026, pp. e759-e769, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561.
Chicago — 17th, bibliography
Mishra, Asheesh, Devendra Singh Rathore, and Vivek Richhariya. "Lung Cancer Classification and Prediction with CNN Deep Learning Technique." International Journal of Creative Research Thoughts 14, no. 4 (2026): e759-e769. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561.
Harvard — author–date
Mishra, A., Rathore, D.S. and Richhariya, V. (2026) 'Lung Cancer Classification and Prediction with CNN Deep Learning Technique', International Journal of Creative Research Thoughts, 14(4), pp. e759-e769. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561
IEEE — numbered reference
A. Mishra, D. S. Rathore and V. Richhariya, "Lung Cancer Classification and Prediction with CNN Deep Learning Technique," IJCRT, vol. 14, no. 4, pp. e759-e769, Apr. 2026.
Vancouver — biomedical
Mishra A, Rathore DS, Richhariya V. Lung Cancer Classification and Prediction with CNN Deep Learning Technique. IJCRT. 2026 Apr;14(4):e759-e769.
AMA — 11th edition
Mishra A, Rathore DS, Richhariya V. Lung Cancer Classification and Prediction with CNN Deep Learning Technique. IJCRT. 2026;14(4):e759-e769. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2604561,
author = {Asheesh Mishra and Devendra Singh Rathore and Vivek Richhariya},
title = {Lung Cancer Classification and Prediction with CNN Deep Learning Technique},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {4},
pages = {e759-e769},
year = {2026},
month = {April},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Mishra, Asheesh
AU - Rathore, Devendra Singh
AU - Richhariya, Vivek
TI - Lung Cancer Classification and Prediction with CNN Deep Learning Technique
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 4
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561
SP - e759-e769
ER -
Issue
Volume 14 Issue 4,
April-2026
Pages : e759-e769
Article Information
- Pages
- e759-e769
- Published
- April 2026
- Registration ID
- IJCRT_305688
- Published Paper ID
- IJCRT2604561
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Bhopal, MP, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 153
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604561
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2604561.pdf
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International Journal of Creative Research Thoughts
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2320-2882
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2013
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Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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