Deep reinforcement learning for automated radiation adaptation in lung cancer

An automated dose adaptation by DRL is a feasible and a promising approach for achieving similar results to those chosen by clinicians, and development of this framework into a fully credible autonomous system for clinical decision support would require further validation on larger multi‐institutional datasets.