Lung Cancer Detection with Machine Learning and Deep Learning: A Narrative Review

Abstract

Lung cancer is the most common cancer-related cause of death worldwide. Unfortunately, current diagnostic techniques often lack sensitivity and precision, leading to delayed diagnoses and ineffective treatments. To diagnose lung cancer, doctors currently mainly rely on the clinical characteristics of their patients and imaging characteristics. However, these techniques have limitations in fully and promptly detecting lesions. Nevertheless, with the help of artificial intelligence (AI), lung cancer treatment, prognosis prediction, and diagnostics can be greatly improved. This paper provides an overview of the role that AI can play in simplifying tasks, while reducing the effort required of radiologists and increasing the accuracy of nodule detection.