A Comparative Study Based on Lung Cancer with Deep Learning and Machine Learning Models

The incredible study of the medical health system is a wide range of computer systems to generate the latest innovations. These innovations are very important for the well-organized implementation of treatment systems that deal with the automatic diagnosis of health problems. The most important health tests can be obtained to predict cancer, which has different forms and can affect different parts of the body. In accordance with the technical development and the latest trend considered, we decided to study the term biomedical, i.e., lung cancer screening. Recently, COVID-19 has been severe in lung cancer patients (70% were hospitalized and 30% passed). Even though severe, COVID-19 reported a small proportion of all lung cancer deaths throughout the pandemic (11% in total). This section presents in-depth training research designed for lung disease recognition in medical imaging. The objectives of this research take place to provide a taxonomy of up-to-date lung disease detection systems based on extensive training, to represent patterns in contemporary work in the field, and to identify remaining challenges and possible future approaches in this theme. Countryside. The proposed future route could improve the number of applications for deep lung disease detection while improving efficiency.