article · Advances in Radiation Oncology
Failure Mode and Effects Analysis (FMEA) is widely used in radiation oncology to proactively identify and mitigate risks, but it is time-consuming and depends heavily on expert experience.This study evaluated whether large language models (LLMs) can supplement traditional expert-driven FMEA by identifying novel failure modes within the Radiation Planning Assistant (RPA) workflow. Methods and MaterialsA multidisciplinary team of board-certified medical physicists, quality assurance engineers, and software developers independently used four LLMs (ChatGPT-4, Gemini
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DOI: 10.1016/j.adro.2026.102060
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