CNN Architecture for Lung Cancer Detection

ABSTRACT

Lungs play major role for the respiratory rate in a human being. Lung cancer can be detected only after the disease spreads to neighboring parts and hence detecting lung cancer in initial stage is difficult. Even in covid-19, lung gets affected as it deals with respiration which is the first symptom in serious covid conditions. In this paper, we have proposed a method to detect the lung cancer which involves feature extraction and ML algorithm or in another way using CNN architecture which is a DL algorithm helps in lung cancer detection. As the methods deal with binary classification which confirms yes/no of the lung cancer presence in human body, both SVM and CNN methods are simpler than any other ML/DL algorithms for this lung cancer data considered. Simulations are carried out in google colab. Feature extraction is carried out for ML algorithm and bar graph, histograms are plotted. © 2022 IEEE.