Deep Learning-Based Automated Detection of Lung Cancer from CT Scans: A Comparative Study

Abstract

ABSTRACT

Lung cancer is one of the leading causes of death resulting from the disease on a global scale. In order to provide effective therapy and achieve better outcomes for patients, early detection and diagnosis are essential. Deep learning (DL) algorithms have demonstrated significant promise in recent years for their use in medical imaging analysis, particularly in the detection and diagnosis of lung cancer. This paper includes a comparative comparison of a number of different DL based models for the automated diagnosis of lung cancer from computed tomography (CT) data.