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

Autor:	Krolik, Jack, Mahal, Herprit, Ahmad, Feroz, Trivedi, Gaurav, Saket, Bahador
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language Computer Science - Machine Learning I.2.7 J.3
Druh dokumentu:	Working Paper
Popis:	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. While the findings suggest promising results, further research is needed to address more specific or complex questions that were beyond the scope of this initial investigation. Comment: 10 pages, 3 figures, 3 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2409.01941 Zobrazit plný text záznamu View this record from Arxiv