Lung malignant growth is one of the most threatening ailments affecting most of the nations in the world, and detection in earlier stages has been a challenge. Early detection can help in saving many lives. This paper shows a methodology that uses a convolutional neural network (CNN) in machine learning for the detection of tumours in the lung. The specificity of the model is desirable and dependable and increasingly productive in contrast to the accuracy shown by conventional neural system frameworks.
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