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1. NRG Oncology Assessment of Artificial Intelligence Deep Learning–Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions

3. Repeatability of Radiomic Features Against Simulated Scanning Position Stochasticity Across Imaging Modalities and Cancer Subtypes: A Retrospective Multi-institutional Study on Head-and-Neck Cases

8. Investigating Long-term Prognostication of CT-based Radiomics for Subgroup of High-risk Localized Prostate Cancer Patients Treated by Whole-pelvic Radiotherapy

9. Investigating Long-term Prognostication of CT-based Radiomics for Subgroup of High-risk Localized Prostate Cancer Patients Treated by Whole-pelvic Radiotherapy

21. Radiation Therapy for Rectal Cancer: Executive Summary of an ASTRO Clinical Practice Guideline

24. Fluence Map Prediction Using Deep Learning Models – Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy

34. The Role of In-Room kV X-Ray Imaging for Patient Setup and Target Localization

38. Machine learning and modeling: Data, validation, communication challenges

41. Improving Quality and Consistency in NRG Oncology Radiation Therapy Oncology Group 0631 for Spine Radiosurgery via Knowledge-Based Planning

45. Establishing the feasibility of the dosimetric compliance criteria of RTOG 1308: phase III randomized trial comparing overall survival after photon versus proton radiochemotherapy for inoperable stage II-IIIB NSCLC

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