Translational AI ConV2X 2023 Panel Discussion
DOI:
https://doi.org/10.30953/thmt.v9.504Keywords:
Artificial intelligence, AI in healthcare, AI in primary care, large language models, LLMs, GPT, solving healthcare administrative challengesAbstract
How do we evaluate large language models for use in healthcare? What are the trusted frameworks for value assessment? Is automation through GPT successfully addressing the healthcare administrative and workforce crisis? What about clinical decision making? Expect a candid discussion from these experts on the implications of LLM’s and AI in Primary Care in the US and around the globe.
Learning Outcomes
• Acquire knowledge of the fundamental principles of large language models
• Understand how these models are trained and deployed in a healthcare context
• Learn how to assess the efficiency and effectiveness of large language models in healthcare
• Understand the measures used in determining the success of these models, such as improved patient outcomes, efficiency in operations, and patient satisfaction
• Learn to apply evaluation or translational frameworks in assessing the value of large language models
• Gain insights into how automation, specifically through GPT, is helping to solve healthcare administrative challenges
• Learn about the use of large language models in clinical decision-making
• Understand the strengths and limitations of these models in making clinical decisions, administration, and the ethics
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Copyright (c) 2024 Sandeep Reddy, Alexandre Lebrun, Adam Chee, PhD, Moderator: Dimitris Kalogeropoulos, PhD
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors retain copyright of their work, with first publication rights granted to Telehealth and Medicine Today (THMT).
THMT is published under a Creative Commons Attribution-NonCommercial 4.0 International License.