Paper Title
A Meta Analysis of People Lifestyle Data to Predict Lung Cancer Using Deep Learning Approaches

Abstract
Lung cancer has costed over 500,000 deaths in the past few years in United States. Early screening of Lung cancer using Computer Tomography can reduce the risk of mortality significantly. However, it is wiser to correlate the cause of Lung cancer with the people lifestyle to proactively prevent it rather than diagnosing it. There are volumes of literature studies which uses Computer Tomography images for predicting the lung cancer using Deep learning approaches. However, such approaches can help only in diagnosing whether the patient has lung cancer or not. In this paper, we investigate the strongest correlated features based on the biomarkers dataset of people and predict the early symptoms of lung cancers. This work can aid people in predicting the risk of lung cancer with low-cost machine learning model and in the case of positive patients take the appropriate decisions. Keywords - Lung cancer, Ensemble, Healthcare 5.0, Deep learning.