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欧洲检验医学中人工智能应用的全面调查:当前应用情况与前景

A comprehensive survey of artificial intelligence adoption in European laboratory medicine: current utilization and prospects.

作者信息

Cadamuro Janne, Carobene Anna, Cabitza Federico, Debeljak Zeljko, De Bruyne Sander, van Doorn William, Johannes Elias, Frans Glynis, Özdemir Habib, Martin Perez Salomon, Rajdl Daniel, Tolios Alexander, Padoan Andrea

机构信息

Department of Laboratory Medicine, Paracelsus Medical University Salzburg, Salzburg, Austria.

Laboratory Medicine, IRCCS San Raffaele Scientific Institute, Milan, Italy.

出版信息

Clin Chem Lab Med. 2024 Oct 24;63(4):692-703. doi: 10.1515/cclm-2024-1016. Print 2025 Mar 26.

Abstract

BACKGROUND

As the healthcare sector evolves, Artificial Intelligence's (AI's) potential to enhance laboratory medicine is increasingly recognized. However, the adoption rates and attitudes towards AI across European laboratories have not been comprehensively analyzed. This study aims to fill this gap by surveying European laboratory professionals to assess their current use of AI, the digital infrastructure available, and their attitudes towards future implementations.

METHODS

We conducted a methodical survey during October 2023, distributed via EFLM mailing lists. The survey explored six key areas: general characteristics, digital equipment, access to health data, data management, AI advancements, and personal perspectives. We analyzed responses to quantify AI integration and identify barriers to its adoption.

RESULTS

From 426 initial responses, 195 were considered after excluding incomplete and non-European entries. The findings revealed limited AI engagement, with significant gaps in necessary digital infrastructure and training. Only 25.6 % of laboratories reported ongoing AI projects. Major barriers included inadequate digital tools, restricted access to comprehensive data, and a lack of AI-related skills among personnel. Notably, a substantial interest in AI training was expressed, indicating a demand for educational initiatives.

CONCLUSIONS

Despite the recognized potential of AI to revolutionize laboratory medicine by enhancing diagnostic accuracy and efficiency, European laboratories face substantial challenges. This survey highlights a critical need for strategic investments in educational programs and infrastructure improvements to support AI integration in laboratory medicine across Europe. Future efforts should focus on enhancing data accessibility, upgrading technological tools, and expanding AI training and literacy among professionals. In response, our working group plans to develop and make available online training materials to meet this growing educational demand.

摘要

背景

随着医疗保健行业的发展,人工智能(AI)在提升检验医学方面的潜力日益得到认可。然而,欧洲各实验室对人工智能的采用率和态度尚未得到全面分析。本研究旨在通过对欧洲实验室专业人员进行调查,以填补这一空白,评估他们目前对人工智能的使用情况、可用的数字基础设施以及他们对未来实施的态度。

方法

我们于2023年10月通过欧洲临床实验室科学学会(EFLM)邮件列表进行了一项系统的调查。该调查探讨了六个关键领域:一般特征、数字设备、健康数据获取、数据管理、人工智能进展以及个人观点。我们分析了回复,以量化人工智能的整合情况并确定其采用的障碍。

结果

在426份初始回复中,排除不完整和非欧洲的回复后,有195份被纳入分析。调查结果显示,人工智能的应用有限,必要的数字基础设施和培训存在重大差距。只有25.6%的实验室报告有正在进行的人工智能项目。主要障碍包括数字工具不足、获取全面数据受限以及人员缺乏人工智能相关技能。值得注意的是,受访者对人工智能培训表现出浓厚兴趣,这表明对教育举措有需求。

结论

尽管人们认识到人工智能有潜力通过提高诊断准确性和效率来彻底改变检验医学,但欧洲实验室面临重大挑战。这项调查凸显了对教育项目和基础设施改进进行战略投资的迫切需求,以支持整个欧洲检验医学中人工智能的整合。未来的努力应集中在提高数据可及性、升级技术工具以及扩大专业人员的人工智能培训和知识普及。作为回应,我们的工作组计划开发并提供在线培训材料,以满足这一日益增长的教育需求。

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