HIGHLIGHTS
SUMMARY
To detect areas of the lung that have been affected by cancer, image processing techniques such as noise reduction, feature extraction, identification of damaged regions, and maybe a comparison with data on the medical history of lung cancer are utilized. The methodology section presents accurate classification and prediction of lung cancer using machine_learning and image processingenabled technology. This results in improving image_quality. According to the findings of the researchers, the performance of the machine_learning algorithms in terms of accuracy and precision in the detection of normal and abnormal lung photos has significantly increased. This . . .
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