Preparing healthcare leaders of the digital age with an integrative artificial intelligence curriculum: a pilot study.

IF 3.1 2区 医学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Medical Education Online Pub Date : 2024-12-31 Epub Date: 2024-02-13 DOI:10.1080/10872981.2024.2315684
Soo Hwan Park, Roshini Pinto-Powell, Thomas Thesen, Alexander Lindqwister, Joshua Levy, Rachael Chacko, Devina Gonzalez, Connor Bridges, Adam Schwendt, Travis Byrum, Justin Fong, Shahin Shasavari, Saeed Hassanpour
{"title":"Preparing healthcare leaders of the digital age with an integrative artificial intelligence curriculum: a pilot study.","authors":"Soo Hwan Park, Roshini Pinto-Powell, Thomas Thesen, Alexander Lindqwister, Joshua Levy, Rachael Chacko, Devina Gonzalez, Connor Bridges, Adam Schwendt, Travis Byrum, Justin Fong, Shahin Shasavari, Saeed Hassanpour","doi":"10.1080/10872981.2024.2315684","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) is rapidly being introduced into the clinical workflow of many specialties. Despite the need to train physicians who understand the utility and implications of AI and mitigate a growing skills gap, no established consensus exists on how to best introduce AI concepts to medical students during preclinical training. This study examined the effectiveness of a pilot Digital Health Scholars (DHS) non-credit enrichment elective that paralleled the Dartmouth Geisel School of Medicine's first-year preclinical curriculum with a focus on introducing AI algorithms and their applications in the concurrently occurring systems-blocks. From September 2022 to March 2023, ten self-selected first-year students enrolled in the elective curriculum run in parallel with four existing curricular blocks (Immunology, Hematology, Cardiology, and Pulmonology). Each DHS block consisted of a journal club, a live-coding demonstration, and an integration session led by a researcher in that field. Students' confidence in explaining the content objectives (high-level knowledge, implications, and limitations of AI) was measured before and after each block and compared using Mann-Whitney <i>U</i> tests. Students reported significant increases in confidence in describing the content objectives after all four blocks (Immunology: <i>U</i> = 4.5, <i>p</i> = 0.030; Hematology: <i>U</i> = 1.0, <i>p</i> = 0.009; Cardiology: <i>U</i> = 4.0, <i>p</i> = 0.019; Pulmonology: <i>U</i> = 4.0, <i>p</i> = 0.030) as well as an average overall satisfaction level of 4.29/5 in rating the curriculum content. Our study demonstrates that a digital health enrichment elective that runs in parallel to an institution's preclinical curriculum and embeds AI concepts into relevant clinical topics can enhance students' confidence in describing the content objectives that pertain to high-level algorithmic understanding, implications, and limitations of the studied models. Building on this elective curricular design, further studies with a larger enrollment can help determine the most effective approach in preparing future physicians for the AI-enhanced clinical workflow.</p>","PeriodicalId":47656,"journal":{"name":"Medical Education Online","volume":"29 1","pages":"2315684"},"PeriodicalIF":3.1000,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10868429/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Education Online","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/10872981.2024.2315684","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/13 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence (AI) is rapidly being introduced into the clinical workflow of many specialties. Despite the need to train physicians who understand the utility and implications of AI and mitigate a growing skills gap, no established consensus exists on how to best introduce AI concepts to medical students during preclinical training. This study examined the effectiveness of a pilot Digital Health Scholars (DHS) non-credit enrichment elective that paralleled the Dartmouth Geisel School of Medicine's first-year preclinical curriculum with a focus on introducing AI algorithms and their applications in the concurrently occurring systems-blocks. From September 2022 to March 2023, ten self-selected first-year students enrolled in the elective curriculum run in parallel with four existing curricular blocks (Immunology, Hematology, Cardiology, and Pulmonology). Each DHS block consisted of a journal club, a live-coding demonstration, and an integration session led by a researcher in that field. Students' confidence in explaining the content objectives (high-level knowledge, implications, and limitations of AI) was measured before and after each block and compared using Mann-Whitney U tests. Students reported significant increases in confidence in describing the content objectives after all four blocks (Immunology: U = 4.5, p = 0.030; Hematology: U = 1.0, p = 0.009; Cardiology: U = 4.0, p = 0.019; Pulmonology: U = 4.0, p = 0.030) as well as an average overall satisfaction level of 4.29/5 in rating the curriculum content. Our study demonstrates that a digital health enrichment elective that runs in parallel to an institution's preclinical curriculum and embeds AI concepts into relevant clinical topics can enhance students' confidence in describing the content objectives that pertain to high-level algorithmic understanding, implications, and limitations of the studied models. Building on this elective curricular design, further studies with a larger enrollment can help determine the most effective approach in preparing future physicians for the AI-enhanced clinical workflow.

通过人工智能综合课程培养数字时代的医疗保健领导者:一项试点研究。
人工智能(AI)正被迅速引入许多专科的临床工作流程。尽管有必要培养了解人工智能的用途和影响的医生,并缩小日益扩大的技能差距,但对于如何在临床前培训期间向医学生最好地介绍人工智能概念,目前还没有达成共识。本研究考察了 "数字健康学者"(DHS)试点非学分强化选修课的效果,该选修课与达特茅斯盖瑟尔医学院的一年级临床前课程同步,重点介绍人工智能算法及其在同时出现的系统模块中的应用。从 2022 年 9 月到 2023 年 3 月,10 名自主选择的一年级学生参加了与四个现有课程模块(免疫学、血液学、心脏病学和肺病学)并行的选修课程。每个 DHS 板块包括一个期刊俱乐部、一个现场编码演示和一个由该领域研究人员主持的整合课程。在每个模块前后,都对学生解释内容目标(人工智能的高级知识、意义和局限性)的信心进行了测量,并使用 Mann-Whitney U 检验进行了比较。在所有四个模块之后,学生们都表示在解释内容目标方面的信心有了明显的提高(免疫学:U=4.5,p=0.030;血液学:U=1.0,p=0.009;心脏病学:U=4.0,p=0.019;肺病学:U=4.0,p=0.030),以及对课程内容评分的平均总体满意度为 4.29/5。我们的研究表明,在院校临床前课程中同时开设数字健康强化选修课,并将人工智能概念嵌入相关临床课题中,可以增强学生对所学模型的高层次算法理解、意义和局限性等内容目标的信心。在这一选修课程设计的基础上,进一步开展更大规模的研究,有助于确定最有效的方法,帮助未来的医生为人工智能增强型临床工作流程做好准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Medical Education Online
Medical Education Online EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
6.00
自引率
2.20%
发文量
97
审稿时长
8 weeks
期刊介绍: Medical Education Online is an open access journal of health care education, publishing peer-reviewed research, perspectives, reviews, and early documentation of new ideas and trends. Medical Education Online aims to disseminate information on the education and training of physicians and other health care professionals. Manuscripts may address any aspect of health care education and training, including, but not limited to: -Basic science education -Clinical science education -Residency education -Learning theory -Problem-based learning (PBL) -Curriculum development -Research design and statistics -Measurement and evaluation -Faculty development -Informatics/web
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信