To evaluate agreement between LLMs and expert reviewers in triaging radiation oncology incident learning system (ILS) forms with regard to three clinically relevant dimensions (workflow process step, severity, and dosimetric impact), with the goal of improvin...
Author profile
Chengyin Li, PhD
Henry Ford Health
Large Language Model-Guided Triage of Incident Learning System Forms In Radiation Oncology
Poster Program · Therapy Physics
Evaluating Vision Language Model for Autonomous Offline Adaptive Radiotherapy Decision Support In Head and Neck Cancers
Current automated offline triggers for adaptive radiotherapy often function as black boxes and fail to provide the reasoning behind a decision. Vision Language Models (VLM) offer a novel solution by providing a clear path toward explainability regarding the d...
Poster Program · Therapy Physics
Disentangling Patient-Specific Canonical Anatomy and Deformation Manifolds for Improved MRI-Guided Adaptive Radiotherapy Segmentation
Accurate organ-at-risk segmentation remains a critical bottleneck in MR-guided adaptive radiotherapy, consuming 20–40 minutes per fraction. Current methods treat each fraction independently, discarding patient-specific information from prior sessions. We deve...
Proffered Program · Diagnostic and Interventional Radiology Physics