Abstract

Lung cancer is a devastating disease with high mortality rates worldwide. Early diagnosis plays a critical role in improving patient outcomes and enhancing treatment efficacy. This abstract provides a concise overview of the recent advancements in lung cancer diagnosis, focusing on innovative modalities and biomarkers that have revolutionized early detection and personalized management. The abstract highlights the significance of imaging technologies, molecular biomarkers, and minimally invasive procedures in the early identification of lung cancer. Additionally, it discusses the emerging role of artificial intelligence in refining diagnostic accuracy and the potential future directions in lung cancer diagnosis. This comprehensive review aims to provide healthcare professionals and researchers with a current understanding of the state-of-the-art techniques available to optimize lung cancer diagnosis and treatment planning.

Keywords: Lung cancer; Diagnosis; Early detection; Imaging technologies; Molecular biomarkers; Artificial intelligence; Treatment planning