Medical Physics Seminar - Wei Liu

Within the complex landscape of cancer therapeutics, radiation oncology stands as a critical component, leveraging multi-dimensional treatment strategies. The rapid evolution and integration of Artificial Intelligence (AI) into this field have catalyzed significant advancements, notably in enhancing the precision, conformity, and operational efficiency of radiation oncology. However, the deployment of AI in standard clinical practice encounters notable hurdles, predominantly its suboptimal performance in managing non-standard, outlier oncological cases. The advent of Artificial Generative Intelligence (AGI) marks a significant shift in this arena. AGI, distinguished by its advanced capabilities in few-shot and zero-shot learning, offers a pathway towards developing highly robust and generalizable AI models. These models are imperative for seamless and effective integration into the various facets of radiation oncology. This presentation delves into the transformative potential of AGI across the entire spectrum of radiation therapy processes, encompassing stages such as initial patient consultation, imaging and simulation, intricate treatment planning, plan approval alongside stringent quality assurance, precise radiation delivery, and comprehensive patient follow-up. Through this exploration, we aim to demonstrate how AGI can substantially enhance the efficacy of radiation therapy, ultimately leading to improved treatment outcomes for cancer patients.