Comparison of ChatGPT vs. Bard to Anesthesia-related Queries

Author:

Patnaik Sourav S.ORCID,Hoffmann Ulrike

Abstract

AbstractWe investigated the ability of large language models (LLMs) to answer anesthesia related queries prior to surgery from a patient’s point of view. In the study, we introduced textual data evaluation metrics, investigated “hallucinations” phenomenon, and evaluated feasibility of using LLMs at the patient-clinician interface. ChatGPT was found to be lengthier, intellectual, and effective in its response as compared to Bard. Upon clinical evaluation, no “hallucination” errors were reported from ChatGPT, whereas we observed a 30.3% error in response from Bard. ChatGPT responses were difficult to read (college level difficulty) while Bard responses were more conversational and about 8thgrade level from readability calculations. Linguistic quality of ChatGPT was found to be 19.7% greater for Bard (66.16 ± 13.42 vs. 55.27 ± 11.76;p=0.0037) and was independent of response length. Computational sentiment analysis revelated that polarity scores of on a Bard was significantly greater than ChatGPT (mean 0.16 vs. 0.11 on scale of −1 (negative) to 1 (positive);p=0.0323) and can be classified as “positive”; whereas subjectivity scores were similar across LLM’s (mean 0.54 vs 0.50 on a scale of 0 (objective) to 1 (subjective),p=0.3030). Even though the majority of the LLM responses were appropriate, at this stage these chatbots should be considered as a versatile clinical resource to assist communication between clinicians and patients, and not a replacement of essential pre-anesthesia consultation. Further efforts are needed to incorporate health literacy that will improve patient-clinical communications and ultimately, post-operative patient outcomes.

Publisher

Cold Spring Harbor Laboratory

Reference84 articles.

1. Current Understanding of Patients’ Attitudes Toward and Preparation for Anesthesia

2. Anesthesiologist to Patient Communication: A Systematic Review;JAMA Netw Open,2020

3. ChatGPT. ChatGPT (Mar 23, 2023 version) [Large language model]. https://chat.openai.com/chat. 2023.

4. Bard. Google Bard (Experimental version) [Large language model]. https://bard.google.com/. 2023.

5. Aldridge, M.J. and R. Penders , Artificial intelligence and anaesthesia examinations: exploring ChatGPT as a prelude to the future. Br J Anaesth, 2023.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Analyzing the Future of ChatGPT in Medical Research;Artificial Intelligence Applications Using ChatGPT in Education;2023-09-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3