Lung Cancer Detection using Hyper Parameter Tuned Convolution Neural Network

Registration ID: IJNRD_211789

Published ID: IJNRD2312397

DOI: Click Here to Get

Shloka Bhattacharyya

Artificial Intelligence, Machine Learning, Deep learning, Decision Tree, Convolutional Neural Network (CNN), Grid Search Cross Validation

- Lung cancer is a life-threatening disease; early identification of lung cancer increases the chances of successful treatment for patients. Imaging techniques generally followed for lung cancer detection are X-ray, Computed tomography (CT), and histopathological images. However, CT scan images are more reliable in detecting lung cancer; this paper focused on lung cancer detection as a ternary classification problem using CT scan images. This paper proposes classifying lung images as 'normal,' 'benign,' and 'malignant,' which helps doctors treat patients effectively. This ternary classification is proposed through deep learning models. Deep Neural Network (DNN), Long Short Term Memory (LSTM), and Convolutional Neural Network (CNN) were used. Experimental results showed more promising results on the CNN algorithm than other models. Thus, the CNN algorithm is enhanced using hyper parameter tuning, and HT-CNN is proposed. To improve the novelty of work and get high detection accuracy for the ternary classification of lung cancer, hyper parameter tuning with Grid search cross-validation technique is proposed. The GSCV identifies the best-fit parameter for deep learning models and enhances the algorithm's performance. Experimental results showed that CT images were normal, benign, and malignant for ternary classes of the lung with deep learning models DNN, LSTM, CNN, and HT-CNN. The results are compared, showing that the hyper-tuned CNN model has achieved the highest accuracy, 99.4%.

Published Paper   E-Certificate

Shloka Bhattacharyya (December-2023). Lung Cancer Detection using Hyper Parameter Tuned Convolution Neural Network . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(12), d867-d873. https://ijnrd.org/papers/IJNRD2312397.pdf

Volume 8 Issue 12, December-2023

Pages : d867-d873

Paper Reg. ID: IJNRD_211789

Published Paper Id: IJNRD2312397

Downloads: 000121978

Research Area: Life Sciences 

Country: Malvern, PA, United States

Published Paper PDF: https://ijnrd.org/papers/IJNRD2312397.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2312397

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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