Artificial intelligence in studies related to programmed cell death protein PD-L1 in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC), the most common subtype of lung cancer, accounts for approximately 85% of all cases. Significant advances are being made in the diagnosis and treatment of NSCLC, especially with the help of molecular translational research. Programmed cell death ligand 1 (PD-L1) is an important cell surface protein that plays a central role in many types of cancer. It is considered the gold standard predictive biomarker for immunotherapy selection in advanced NSCLC patients. In clinical studies, protein profiling and immunofluorescence methods are promising for routine PD-L1-related tests and advances in this field have been accelerating with the help of artificial intelligence (AI). Machine learning (ML), a subset of AI, is defined as a method of analyzing sample data with a target task, parsing this data into predictive models and clustering it on its own, and then analyzing it by the computer. As the most used method for predicting efficiency and analyzing multi-omics data, ML has been one of the promising developments in evidence-based medicine. Many prediction models based on ML algorithms are used today due to the development and widespread use of digital images. Research shows that AI has made progress in early diagnosis and screening of NSCLC and in evaluating immunotherapy effectiveness and prognosis. It is anticipated that future research and AI methods will advance the diagnosis and treatment of NSCLC even with a single marker. [ABSTRACT FROM AUTHOR]