A systematic Review and Analysis: The Impact of Air Pollution on Lung Cancer

Toxic chemicals and contaminants abound in urban surroundings that have seen a high level of industrialization. They have the potential to have severe impacts on human health, producing both acute and chronic disorders such as respiratory infections, lung cancer, and cardiovascular disease. It is critical to monitor air pollution in order to educate individuals about the health hazards associated with air pollutants, as well as to aid policymakers in developing rules and legislation that try to reduce those health risks. Lung cancer, along with prostate, oral, and breast cancer, is the most frequent kind of cancer in the world. Both men and women develop cancer as a result of cigarette smoking, excessive pollution, and inhalation of cancer-causing agents. Nonetheless, males are more likely than women to get cancer. To make diagnoses, many imaging modalities such as CT scans, magnetic resonance imaging (MRI), PET scanning, and X-rays are employed in conjunction with one another. Using grayscale saturation in images, oncologists and physicians are able to identify cancer. In addition to prior experience in human anatomy and physiology, it is necessary to be knowledgeable about imaging techniques. Because of a lack of imaging knowledge, diagnosis takes an excessive amount of time and produces worse accuracy. This research work can utilize a Modified Convolutional Neural Network method (MCNN), to predict the occurrence of different forms of lung cancer in different individuals to study about the high impact of Air pollution. This research study will train MCNN using features derived from lung CT scans, and evaluate their performance employing performance metrics collected from the CT images.