A study of criteria‐based online adaptive radiotherapy with radiomics and dosimetry for postoperative prostate cancer

This study is the first to combine radiomics and dosimetric features using machine learning to establish a triggered OART prediction model, demonstrating the feasibility of using CT radiomics and dosimetric features for OART trigger prediction. By employing model integration techniques, we addressed the issue of one-dimensional feature bias, significantly enhancing model performance. This research provides new data analysis methods for adaptive radiotherapy triggering in postoperative prostate cancer, offering substantial clinical value.