ABSTRACT
The purpose of this chapter is to highlight the role of artificial intelligence (AI) in detecting pulmonary cancer in the early stages. Early detection of lung cancer is very important for the survival of the individual. In this chapter the focus is on detection of early-stage lung cancer using deep neural networks. Basically, cancer detection can be done through CT scans, but using 3D-Unet and reference images given to a dataset, we can train a model to give an accurate result. AI can be helpful for detection of cancer more accurately than humans, which can be beneficial to patients and healthcare with a minimal amount of time requirement. Pulmonary cancer is one of the major causes of cancer-related deaths due to its aggressive nature and delayed detection at advanced stages. Early detection of lung cancer is very important for the survival of an individual and is a significant challenging problem. Basically, chest radiographs, which include x-rays and computed tomography (CT), are used initially for the diagnosis of the malignant nodules. At the earlier stage, the benign and the malignant nodules show a very close resemblance to each other. This deep neural network model for nodule detection and classification, combined with clinical factors, helps in the reduction of misdiagnosis and false-positive (FP) results in early-stage lung cancer diagnosis. This chapter highlights the importance of AI in the healthcare industry in detecting cancer at an early stage without any human interaction with minimal errors and the highest accuracy.
