Abstract: We all know about various types of hazardous diseases but out of them all the Cancer is the most fatal and common among people. A large number of population get suffered and lose their lives due to it. If cancer is diagnosed in early stages it could be cured, but if it diagnosed in later stages, the chances of survival became negligible.The prominent cause of cancer-related mortality throughout the world is "Lung Cancer". Hence beforehand detection, prediction and diagnosis of lung cancer is a necessity as it can increase the chances of survival .Various types of machine learning algorithms (ML) like Naive Bayes, Support Vector Machine (SVM), Logistic regression, Artificial Neural Network (ANN), Convulational Neural Network (CNN) have been applied in the healthcare sector for analysis and prognosis of lung cancer. This paper will highlight the methods by which we can diagnosis or predict the presence of the tumor in the lungs using image data.
Keywords: Lung Cancer, Entropy, Classification, Thresholding, Tumor, Histogram, Segmentation, Dilation.
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DOI:
10.17148/IJARCCE.2022.11589
