The Needs and Benefits of Continuous Model Updates on the Accuracy of RT-induced Toxicity Prediction Models within a Learning Health System.

Our preliminary results demonstrate that updating prediction models with prospective data collection is effective for maintaining the performance of xerostomia prediction. This suggests that a machine learning framework can handle the dynamic changes in a radiation oncology clinical practice and may be an important component for the construction of a learning health system.