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A Rapid Learning Approach to the Knowledge Modeling of Radiation Therapy Planning

      The purpose of this study was to implement a rapid learning method to train knowledge models to predict the organ-at-risk (OAR) dose sparing in radiation therapy (RT) based on an array of patient anatomical features. We also aimed to establish the evaluation criteria and validation method to ensure the accuracy and the efficiency of the learning process.
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