  The emergence of artificial general intelligence (AGI) is transforming
radiation oncology. As prominent vanguards of AGI, large language models (LLMs)
such as GPT-4 and PaLM 2 can process extensive texts and large vision models
(LVMs) such as the Segment Anything Model (SAM) can process extensive imaging
data to enhance the efficiency and precision of radiation therapy. This paper
explores full-spectrum applications of AGI across radiation oncology including
initial consultation, simulation, treatment planning, treatment delivery,
treatment verification, and patient follow-up. The fusion of vision data with
LLMs also creates powerful multimodal models that elucidate nuanced clinical
patterns. Together, AGI promises to catalyze a shift towards data-driven,
personalized radiation therapy. However, these models should complement human
expertise and care. This paper provides an overview of how AGI can transform
radiation oncology to elevate the standard of patient care in radiation
oncology, with the key insight being AGI's ability to exploit multimodal
clinical data at scale.
