CEACAM5 and lung cancer: On the other hand, the feature recognition machine learning model identified eight features, including age, smoking or frequent passive smoking, significant psychological stress in the past year, occupational exposure (presence of air pollution in the work environment), presence of chronic lung disease, family history of lung cancer, decreased levels of albumin, and elevated levels of carcinoembryonic antigen.