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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 3 | Month- March 2026
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Published Paper Details:
Paper Title
Lung Cancer Classification Using Deep Learning: An Optimized CNN Approach
Authors
Harshal Papal, Madhura Mhatre, Rohan Patil, Suhail Pathan, Balaji chaugule
Keywords
Lung Cancer Detection, Convolutional Neural Network (CNN), Deep Learning, Medical Image Processing, Classification
Abstract
: Lung cancer is one of the most prevalent and life-threatening diseases worldwide, contributing to a significant number of cancer-related deaths. Early detection is crucial in improving survival rates, yet traditional diagnostic methods such as biopsies and CT scans can be both time-consuming and require specialized expertise. With the rise of deep learning, Convolutional Neural Networks (CNNs) have emerged as a powerful tool in medical imaging, enabling automated and accurate classification of lung cancer from medical scans. This study presents an optimized CNN model, trained using the NIH Lung Image dataset, with enhanced preprocessing and hyperparameter tuning to maximize accuracy. The results indicate that the proposed approach can classify lung cancer efficiently, potentially assisting medical professionals in making faster and more reliable diagnoses.
IJCRT's Publication Details
Unique Identification Number - IJCRT2503147
Paper ID - 278573
Page Number(s) - b261-b270
Pubished in - Volume 13 | Issue 3 | March 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Harshal Papal, Madhura Mhatre, Rohan Patil, Suhail Pathan, Balaji chaugule, "Lung Cancer Classification Using Deep Learning: An Optimized CNN Approach", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 3, pp.b261-b270, March 2025, Available at :http://www.ijcrt.org/papers/IJCRT2503147.pdf
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Volume 14 | Issue 3
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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