Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer

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Abstract
Globally, lung cancer has been the most commonly diagnosed cancer and leading cause of cancer-related deaths for several decades (not counting skin cancer).1 In the United States, the current 5-year survival rate is approximately 20.6%.2 Patients with lung cancer have different outcomes based on various clinical factors.3-6 A 2020 study7 using data from Surveillance, Epidemiology, and End Results (SEER) found a significant reduction in mortality for lung cancer from 2013 to 2016, which was potentially associated with incidence reduction along with treatment advances. A large cohort with adequate clinical information is necessary to identify stable and reliable prognostic variables and the factors associated with improved survival outcomes.

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