6 papers
The Daily Dose: Workflow-Integrated Large Language Model Automation for Clinical Summarization and Trial Identification in Radiation Oncology
Jason Holmes, Federico Mastroleo, Mariana Borras-Osorio +17
Objective: To describe the design and early clinical evaluation of The Daily Dose (TDD), an LLM-driven, automated clinical summarization and clinical-trial identification system in…
RadOnc-GPT: An Autonomous LLM Agent for Real-Time Patient Outcomes Labeling at Scale
Jason Holmes, Yuexing Hao, Mariana Borras-Osorio +22
Manual labeling limits the scale, accuracy, and timeliness of patient outcomes research in radiation oncology. We present RadOnc-GPT, an autonomous large language model (LLM)-based…
AI in Proton Therapy Treatment Planning: A Review
Yuzhen Ding, Hongying Feng, Martin Bues +12
Purpose: Proton therapy provides superior dose conformity compared to photon therapy, but its treatment planning is challenged by sensitivity to anatomical changes, setup/range unc…
Causal Machine Learning Analysis of Empirical Relative Biological Effectiveness (RBE) for Mandible Osteoradionecrosis in Head and Neck Cancer Radiotherapy
Jingyuan Chen, Zhong Liu, Yunze Yang +8
Mandible Osteoradionecrosis (ORN) is one of the most severe adverse events (AEs) for head and neck (H&N) cancer radiotherapy. Previous retrospective investigations on real-world da…
Diffusion Transformer-based Universal Dose Denoising for Pencil Beam Scanning Proton Therapy
Yuzhen Ding, Jason Holmes, Hongying Feng +13
Purpose: Intensity-modulated proton therapy (IMPT) offers precise tumor coverage while sparing organs at risk (OARs) in head and neck (H&N) cancer. However, its sensitivity to anat…
Critical review of patient outcome study in head and neck cancer radiotherapy
Jingyuan Chen, Yunze Yang, Chenbin Liu +8
Rapid technological advances in radiation therapy have significantly improved dose delivery and tumor control for head and neck cancers. However, treatment-related toxicities cause…