The untapped potential of artificial intelligence to manage lung cancer

Abstract

Lung cancer, the second most common cancer globally, is a leading cause of cancer-related deaths, with high treatment costs and a median survival of only 14 months. Delayed diagnosis, with most cases detected at advanced stages, contributes significantly to its morbidity and mortality. Early detection has been shown to improve survival rates. Artificial intelligence (AI) offers a promising solution, successfully aiding in early lung cancer detection, staging, treatment selection, and prognosis prediction. To date, AI has been applied to various aspects of lung cancer management, including diagnosis, cancer staging, treatment, and prognosis determination. However, the use of AI remains limited and faces several challenges in its clinical application, such as the need for high-quality data, broader validation, integration with existing healthcare systems, and acceptance by healthcare professionals and patients. This review aims to determine the role of AI in lung cancer management and also identify current limitations and challenges in its clinical application.