Role of artificial intelligence in the care of patients with nonsmall cell lung cancer

Abstract

Lung cancer is the leading cause of cancer death worldwide. In up to 57% of patients, it is diagnosed at an advanced stage and the five-year survival rate ranges between 10 to 16%. There has been a significant amount of research using machine learning to generate tools using patient data to improve outcomes. This narrative review is based on research material obtained from PubMed up to Nov 2017. The search terms include “artificial intelligence”, “machine learning”, “lung cancer”, “Non-Small Cell Lung Cancer (NSCLC)”, “diagnosis”, “treatment”. Recent studies support the use of computer-aided systems and the use of radiomic features in order to help diagnose lung cancer earlier. Other studies have looked at machine learning (ML) methods that offer prognostic tools to doctors and help them in choosing personalized treatment options for their patients based on molecular, genetics, and histological features. Combining artificial intelligence approaches into healthcare may serve as a beneficial tool for patients with NSCLC and this review outlines these benefits and current shortcomings throughout the continuum of care. We present a review of the various applications of ML methods in NSCLC as it relates to improving diagnosis, treatment and outcomes.