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Translational AI ConV2X 2023 Panel Discussion

By
Sandeep Reddy ,
Sandeep Reddy

MBA (Healthcare Management), Deakin School of Medicine

Medi-AI

Alexandre Lebrun ,
Alexandre Lebrun

Nabla

Adam Chee, PhD ,
Adam Chee, PhD

Smart Health Leadership Centre, Institute of Systems Science National University of Singapore

Moderator: Dimitris Kalogeropoulos, PhD
Moderator: Dimitris Kalogeropoulos, PhD

Global Health and Digital Innovation Foundation

Abstract

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

Citation

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

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