Randomised controlled trials, including the National Lung Screening Trial (NLST) and the
NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT …

The responses of patients to tumor therapies vary due to tumor heterogeneity. Tumor
stratification has been attracting increasing attention for accurately distinguishing between …

Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

Non-small-cell lung cancer (NSCLC) is one of the most frequent cancer types and is
responsible for the majority of cancer-related deaths worldwide. The management of …

Low-dose computer tomographic (LDCT) lung cancer screening reduces lung cancer–
specific and all-cause mortality among high-risk individuals, but implementation has been …

Lung cancer is a fatal disease with a high mortality rate in diseased patients. Early diagnosis
of this disease and accurately identifying the lung cancer stage can save the patients' lives …

Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

Recent advancements in artificial intelligence (AI) have precipitated significant
breakthroughs in healthcare, particularly in refining diagnostic procedures. However …

The implementation of low-dose chest CT for lung screening presents a crucial opportunity
to advance lung cancer care through early detection and interception. In addition, millions of …

Simple Summary In this comprehensive review, we aimed to summarize the advances made
by artificial intelligence in the field of lung cancer screening, diagnosis, and management …