Towards Leveraging Large Language Models for Automated Medical Q&A Evaluation

Understand

This paper explores the potential of using Large Language Models (LLMs) to automate the evaluation of responses in medical Question and Answer (Q\&A) systems, a crucial form of Natural Language Processing.

• Traditionally, human evaluation has been indispensable for assessing the quality of these responses.
• However, manual evaluation by medical professionals is time-consuming and costly.
• Our study examines whether LLMs can reliably replicate human evaluations by using questions derived from patient data, thereby saving valuable time for medical experts.