Developing Effective Frameworks for Large Language Model-Based Medical Chatbots: Insights From Radiotherapy Education With ChatGPT.

James C L Chow, Kay Li
Author Information
  1. James C L Chow: Department of Medical Physics, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada. ORCID
  2. Kay Li: Department of English, Faculty of Arts and Science, University of Toronto, Toronto, ON, Canada. ORCID

Abstract

This Viewpoint proposes a robust framework for developing a medical chatbot dedicated to radiotherapy education, emphasizing accuracy, reliability, privacy, ethics, and future innovations. By analyzing existing research, the framework evaluates chatbot performance and identifies challenges such as content accuracy, bias, and system integration. The findings highlight opportunities for advancements in natural language processing, personalized learning, and immersive technologies. When designed with a focus on ethical standards and reliability, large language model-based chatbots could significantly impact radiotherapy education and health care delivery, positioning them as valuable tools for future developments in medical education globally.

Keywords

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MeSH Term

Humans
Radiotherapy
Education, Medical

Word Cloud

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