The STFM Podcast
Bonus Conference Episode: Annual 2024 Closing Session, Generative AI for Research and Education: From Theory to Practice with Tanner Dean, DO
Generative AI for Research and Education: From Theory to Practice
Presented by Tanner Dean, DO, University of Kansas, Wichita
STFM Annual Conference 2024 Closing Session | Wednesday, May 8, 2024
Generative AI, especially tools like ChatGPT, is changing medicine. In this talk, we'll explore ChatGPT's background, its underlying mechanics, and its strengths and weaknesses. Beyond mere understanding, we will explore frameworks needed to safely and efficiently use this technology. Grasping the AI behind ChatGPT as well as best practices will enable us to look at practical uses in primary care research and teaching. This includes using AI for quick Q&A sessions, help in writing, creating visuals, summarizing articles**, and exploring its broader potential.
The future of medical education will blend traditional teaching with AI tools. It's vital for today's educators to have working knowledge of these new technologies. This talk urges primary care professionals to not just watch, but actively join in the AI revolution. By equipping the educators, this talk hopes to inspire participants to dive in to discover the simple yet powerful ways AI can boost their work in medicine. Participants should walk away with a introductory understanding of ChatGPT works, how they can write effective prompts and several ways they can use ChatGPT in their practice.
Learning Objectives: At the end of the session each participant should...
- Explain the methodology and principles behind how ChatGPT is trained.
- Identify common pitfalls and limitations associated with ChatGPT and similar AI models.
- Recognize several various potential uses of ChatGPT in a research and teaching environment.
- Discuss the predicted trajectory and role of ChatGPT in the future landscape of primary care research and education.
Copyright © Society of Teachers of Family Medicine, 2024
Tanner Dean, DO:
Dr. Tanner Dean is an Assistant Professor of Internal Medicine at the KU School of Medicine in Wichita. Trained as a Doctor of Osteopathic Medicine from A.T. Still University, he completed his Residency in Internal Medicine at KUMC-Wichita. Dr. Dean's unique blend of clinical acumen is further enriched with a certification in Artificial Intelligence (AI) from the American Board of Artificial Intelligence in Medicine. He teaches students both on rotation in the hospital as well as leads the 3rd year neurology clerkship for the KU School of Medicine - Wichita. His research stands at the confluence of technology and medicine. Notably, he has undertaken innovative projects to enhance clinical care through technological advancements. A central theme of his current investigations is understanding physician perceptions of AI in healthcare and the potential of large language learning models in all aspects of medical practice, research, and education. Dr. Dean is very optimistic about AI in healthcare and is working on building the educational structures to equip educators and physicians of the future with the confidence and knowledge to use AI in their medical practice.
