The Detection and Prevention of Lung Cancer using Convolution Neural Networks - A Review

Lung cancer is one among malignancies with high risk of morbidity and mortality ration. In each phase of lung cancer detection imagining plays as vital role to develop imaging based AI models which plays potential key role in detection and customized cancer treatment for the patients. Lung nodule detection by computer aided techniques has recast early detection of lung disease. The feasible use of AI approaches has limitations and more screening program required to detect and identify lung cancer patients with high risk factor. The promising results can be obtained by combining clinical laboratory data and image features using AI models to predict patient’s outcomes, specific therapy responses, risk factor computation and toxic reaction developments etc. In the research review, which provides an overall overview of AI based imagining tools, an automated lesion detection and its characterization, segmentation process, predictions of the outcomes, to provide exact and on time treatment by radiologist and clinicians with the foundations of specific applications in the medical era