Development of an artificial intelligence model to predict survival at specific time intervals for lung cancer patients
Survival prediction models for lung cancer patients could help guide their care and therapy decisions. The objectives of this study were to predict probability of survival beyond 90, 180 and 360 days from any point in a lung cancer patient’s journey. Conclusions showed that an AI model to predict survival of lung cancer patients built using a large real world dataset yielded high accuracy. This general model can further be used to predict survival of sub cohorts stratified by variables such as stage or various treatment effects. Such a model could be a useful for assessing patient risk and treatment options, evaluating cost and quality of care or determining clinical trial eligibility.