Dr Kouzy on the Creation of a Centralized Resource to Inform AI Use in Radiation Oncology

In Partnership With:

Partner | Cancer Centers | <b>The University of Texas MD Anderson Cancer Center</b>

Ramez Kouzy, MD, discusses efforts to improve knowledge of the use of AI in radiation oncology through the creation of an online repository.

Ramez Kouzy, MD, resident physician, Radiation Oncology, The University of MD Anderson Cancer Center, discusses efforts to improve knowledge surrounding the use of artificial intelligence (AI), specifically large language models, in radiation oncology through the creation of an online repository.

Kouzy and his colleagues aimed to develop a comprehensive website dedicated to prompts that enable residents, trainees, and attending physicians to deepen their understanding of large language models and their applications in radiation oncology and general oncology. This project stemmed from increased interest in leveraging large language models and AI for educational purposes within the field of oncology, as well as recognition of the importance of expanding knowledge and best practices in the rapidly evolving field of AI, he explains.

To create this platform, Kouzy and colleagues reviewed existing literature on large language models, techniques, and resources. They then curated and distilled key information into a user-friendly format on the website. The resulting platform serves as a centralized resource for residents, trainees, or attending physicians, condensing and synthesizing the latest research and insights in this dynamic field, making it more accessible for users seeking to enhance their proficiency in AI techniques relevant to oncology, Kouzy states.

By collating this knowledge, Kouzy hopes to facilitate rapid dissemination and comprehension of AI techniques tailored specifically for oncological contexts. Moving forward, Kouzy envisions fostering increased collaboration with AI and language model researchers to explore innovative educational and training applications within oncology.

Future research efforts will focus on evaluating the impact of AI integration through quantitative and qualitative studies, aiming to quantify the benefits of these technologies in enhancing educational outcomes and optimizing clinical practices in oncology, Kouzy expands. This project represents a key step towards advancing the integration of AI into oncology education and practice, with the ultimate goal of improving patient care and advancing oncological research.