对欧洲实验室医学采用人工智能情况的全面调查:当前使用情况和前景。

IF 3.8 2区 医学 Q1 MEDICAL LABORATORY TECHNOLOGY
Janne Cadamuro, Anna Carobene, Federico Cabitza, Zeljko Debeljak, Sander De Bruyne, William van Doorn, Elias Johannes, Glynis Frans, Habib Özdemir, Salomon Martin Perez, Daniel Rajdl, Alexander Tolios, Andrea Padoan
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引用次数: 0

摘要

背景:随着医疗保健行业的发展,人工智能(AI)在提高实验室医疗水平方面的潜力日益得到认可。然而,欧洲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,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,从而填补这一空白:我们在 2023 年 10 月进行了一次有条不紊的调查,通过 EFLM 邮件列表进行分发。调查探讨了六个关键领域:一般特征、数字设备、健康数据访问、数据管理、人工智能进步和个人观点。我们对回复进行了分析,以量化人工智能的整合情况,并找出采用人工智能的障碍:结果:从 426 份初步回复中,在剔除不完整和非欧洲条目后,我们考虑了 195 份回复。调查结果显示,人工智能的参与度有限,在必要的数字基础设施和培训方面存在巨大差距。只有 25.6% 的实验室报告了正在进行的人工智能项目。主要障碍包括数字工具不足、获取全面数据的途径受限以及人员缺乏人工智能相关技能。值得注意的是,人们对人工智能培训表达了浓厚的兴趣,这表明了对教育举措的需求:尽管人工智能在提高诊断准确性和效率方面具有公认的变革实验室医学的潜力,但欧洲的实验室仍面临着巨大的挑战。这项调查凸显了对教育计划和基础设施改善进行战略投资的迫切需要,以支持人工智能在整个欧洲实验室医学中的应用。未来的工作重点应放在提高数据的可访问性、升级技术工具以及扩大专业人员的人工智能培训和扫盲上。为此,我们的工作组计划开发并提供在线培训材料,以满足日益增长的教育需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comprehensive survey of artificial intelligence adoption in European laboratory medicine: current utilization and prospects.

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.

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来源期刊
Clinical chemistry and laboratory medicine
Clinical chemistry and laboratory medicine 医学-医学实验技术
CiteScore
11.30
自引率
16.20%
发文量
306
审稿时长
3 months
期刊介绍: Clinical Chemistry and Laboratory Medicine (CCLM) publishes articles on novel teaching and training methods applicable to laboratory medicine. CCLM welcomes contributions on the progress in fundamental and applied research and cutting-edge clinical laboratory medicine. It is one of the leading journals in the field, with an impact factor over 3. CCLM is issued monthly, and it is published in print and electronically. CCLM is the official journal of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and publishes regularly EFLM recommendations and news. CCLM is the official journal of the National Societies from Austria (ÖGLMKC); Belgium (RBSLM); Germany (DGKL); Hungary (MLDT); Ireland (ACBI); Italy (SIBioC); Portugal (SPML); and Slovenia (SZKK); and it is affiliated to AACB (Australia) and SFBC (France). Topics: - clinical biochemistry - clinical genomics and molecular biology - clinical haematology and coagulation - clinical immunology and autoimmunity - clinical microbiology - drug monitoring and analysis - evaluation of diagnostic biomarkers - disease-oriented topics (cardiovascular disease, cancer diagnostics, diabetes) - new reagents, instrumentation and technologies - new methodologies - reference materials and methods - reference values and decision limits - quality and safety in laboratory medicine - translational laboratory medicine - clinical metrology Follow @cclm_degruyter on Twitter!
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