Evaluation Summary:
This work presents a new model that leverages imaging and non-imaging data for the prediction of the survival of patients with early-stage NSCLC. The new model sought to demonstrate the roles of imaging and non-imaging features in determining high-risk nodes within the graph neural network, and the results have the potential of broad interest to clinicians within the field of cancer and have a high value towards clinical application.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewer remained anonymous to the authors.)