Early diagnosis and risk stratification of lung neoplasms using artificial intelligence models applied to chest tomography: scoping review

This project is a scoping review that aims to synthesize the current evidence on the use of artificial intelligence algorithms applied to chest computed tomography for the early detection, diagnosis, and risk stratification of lung neoplasms. Given the high prevalence and frequent underdiagnosis of lung cancer—the leading cause of cancer mortality worldwide—the review will evaluate the diagnostic performance (e.g., AUC, sensitivity, specificity), validation, and clinical applicability of machine learning and deep learning models in chest CT studies. The findings are expected to identify research gaps and inform the potential integration of AI-based tools into clinical practice, particularly in non-specialized and resource-limited settings.