人工智能对图像驱动医学的承诺:对放射科医生和病理科医生观点的定性访谈研究。

IF 2.6 Q2 HEALTH CARE SCIENCES & SERVICES JMIR Human Factors Pub Date : 2024-11-21 DOI:10.2196/52514
Jojanneke Drogt, Megan Milota, Wouter Veldhuis, Shoko Vos, Karin Jongsma
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引用次数: 0

摘要

背景:放射学和病理学等以图像为驱动的专业处于医疗人工智能(AI)创新的前沿。许多人认为,人工智能将导致专业角色的重大转变,因此,调查专业人员如何看待人工智能创新将引发的未决变化,并将他们的观点纳入正在进行的人工智能开发至关重要:我们的研究旨在深入了解放射科医生和病理科医生对人工智能前景的看法和愿望:我们进行了首次定性访谈研究,调查放射科医生和病理科医生对人工智能融入其领域的看法。研究设计符合定性研究报告综合标准(COREQ):本研究共采访了 21 位参与者(7 位病理学家、10 位放射科医生和 4 位计算机科学家)。访谈显示,受访者对人工智能的影响持有不同的观点。受访者讨论了人工智能给特定任务带来的各种好处;然而,病理学家和放射科医生都认为,人工智能尚未达到其炒作的效果。总之,我们的研究表明,人工智能可以促进图像驱动型专业人员的工作流程发生可喜的变化,并最终提高医疗质量。与此同时,这些专业人士也承认,对人工智能的许多希望和期待不太可能在未来十年内成为现实:本研究指出了对人工智能在影像专业领域的应用前景保持 "健康的怀疑态度 "的重要性,并主张就人工智能是否是解决日常临床实践中遇到的当前问题的正确技术开展更具结构性和包容性的讨论。
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The Promise of AI for Image-Driven Medicine: Qualitative Interview Study of Radiologists' and Pathologists' Perspectives.

Background: Image-driven specialisms such as radiology and pathology are at the forefront of medical artificial intelligence (AI) innovation. Many believe that AI will lead to significant shifts in professional roles, so it is vital to investigate how professionals view the pending changes that AI innovation will initiate and incorporate their views in ongoing AI developments.

Objective: Our study aimed to gain insights into the perspectives and wishes of radiologists and pathologists regarding the promise of AI.

Methods: We have conducted the first qualitative interview study investigating the perspectives of both radiologists and pathologists regarding the integration of AI in their fields. The study design is in accordance with the consolidated criteria for reporting qualitative research (COREQ).

Results: In total, 21 participants were interviewed for this study (7 pathologists, 10 radiologists, and 4 computer scientists). The interviews revealed a diverse range of perspectives on the impact of AI. Respondents discussed various task-specific benefits of AI; yet, both pathologists and radiologists agreed that AI had yet to live up to its hype. Overall, our study shows that AI could facilitate welcome changes in the workflows of image-driven professionals and eventually lead to better quality of care. At the same time, these professionals also admitted that many hopes and expectations for AI were unlikely to become a reality in the next decade.

Conclusions: This study points to the importance of maintaining a "healthy skepticism" on the promise of AI in imaging specialisms and argues for more structural and inclusive discussions about whether AI is the right technology to solve current problems encountered in daily clinical practice.

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来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
期刊最新文献
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