Evaluation of ChatGPT pathology knowledge using board-style questions

Author:

Geetha Saroja D1,Khan Anam1,Khan Atif1,Kannadath Bijun S2,Vitkovski Taisia1

Affiliation:

1. Department of Pathology and Laboratory Medicine, North Shore University Hospital and Long Island Jewish Medical Center, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell Health , Greenvale, NY , US

2. Department of Internal Medicine, University of Arizona College of Medicine , Phoenix, AZ , US

Abstract

Abstract Objectives ChatGPT is an artificial intelligence chatbot developed by OpenAI. Its extensive knowledge and unique interactive capabilities enable its use in various innovative ways in the medical field, such as writing clinical notes and simplifying radiology reports. Through this study, we aimed to analyze the pathology knowledge of ChatGPT to advocate its role in transforming pathology education. Methods The American Society for Clinical Pathology Resident Question Bank 2022 was used to test ChatGPT, version 4. Practice tests were created in each subcategory and answered based on the input that ChatGPT provided. Questions that required interpretation of images were excluded. We analyzed ChatGPT performance and compared it with average peer performance. Results The overall performance of ChatGPT was 56.98%, lower than that of the average peer performance of 62.81%. ChatGPT performed better on clinical pathology (60.42%) than on anatomic pathology (54.94%). Furthermore, its performance was better on easy questions (68.47%) than on intermediate (52.88%) and difficult questions (37.21%). Conclusions ChatGPT has the potential to be a valuable resource in pathology education if trained on a larger, specialized medical data set. Those relying on it (in its current form) solely for the purpose of pathology training should be cautious.

Publisher

Oxford University Press (OUP)

Subject

General Medicine

Reference14 articles.

1. An era of ChatGPT as a significant futuristic support tool: a study on features, abilities, and challenges;Haleem,2022

2. GPT-3: Its nature, scope, limits, and consequences;Floridi,2020

3. Chatbots, ChatGPT, and scholarly manuscripts—WAME recommendations on ChatGPT and chatbots in relation to scholarly publications;Zielinski,2023

4. Evaluating the feasibility of ChatGPT in healthcare: an analysis of multiple clinical and research scenarios;Cascella,2023

5. ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports;Jeblick,2023

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