LUNG CANCER DIAGNOSIS USING MACHINE LEARNING
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Mar 23, 2021
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Abstract
Lung cancer is the world's most lethal and life-threatening disease. Although early identification and accurate treatment are essential to minimize lung cancer death rates. A computed tomography (CT) scan-based picture is one of the finest imaging modalities for lung cancer diagnosis utilizing deep learning algorithms. In this paper, we present a deep learning model based on Convolutional Neural Networks (CNN) for the early diagnosis of lung cancer utilizing CT scan pictures. We also compared our suggested model to various existing models. We discovered that CNN outperformed other models with an accuracy of 95%, an AUC of 96%, a recall of 95%, and a loss of 0.18.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
[1]
Samrajyam Singu and Mahesh Tunguturi, “LUNG CANCER DIAGNOSIS USING MACHINE LEARNING”, IEJRD - International Multidisciplinary Journal, vol. 6, no. 2, p. 15, Mar. 2021.
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