Abstract

Lung cancer contributes a great percentage to the number of cancer-related deaths globally, which mandates science to find ways to improve its approaches to lung cancer diagnosis and treatment. Artificial Intelligence (AI) has emerged in recent times as one of the best solutions to lung cancer diagnosis and treatment. In this essay, attention will be paid to the current roles AIs are performing in lung cancer detection and treatment. Huge successes have been recorded in the use of radiomics, deep learning, and machine learning in lung cancer screening, diagnosis, and treatment. AI has assisted healthcare professionals to better characterize cancer cells and enable them to make better choices regarding treatment procedures. AI has contributed tremendously to the improvement in imaging modalities, including PET-CT imaging, Chest radiography, low-dose CT scans, etc. It also enables healthcare professionals to detect tumor markers and biomarkers in affected patients for a better treatment procedure. However, there is room for improvement. Further studies into the field of AI in lung cancer treatment can help reduce morbidity, mortality, and other potential outcomes.

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