A comprehensive survey of artificial intelligence adoption in European laboratory medicine: current utilization and prospects
Language English Country Germany Media electronic-print
Document type Journal Article
PubMed
39443973
DOI
10.1515/cclm-2024-1016
PII: cclm-2024-1016
Knihovny.cz E-resources
- Keywords
- artificial intelligence, digital medicine, new technologies,
- MeSH
- Laboratories MeSH
- Humans MeSH
- Surveys and Questionnaires MeSH
- Artificial Intelligence * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Europe MeSH
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.
Clinical Institute of Laboratory Diagnostics University Hospital Centre Osijek Osijek Croatia
Department of Diagnostic Sciences Ghent University Ghent Belgium
Department of Laboratory Medicine AZ Sint Blasius Dendermonde Belgium
Department of Laboratory Medicine Paracelsus Medical University Salzburg Salzburg Austria
Department of Medicine University of Padova and University Hospital of Padova Padova Italy
Department of Microbiology Immunology and Transplantation KU Leuven Leuven Belgium
Department of Pharmacology JJ Strossmayer University of Osijek Osijek Croatia
Department of Transfusion Medicine and Cell Therapy Medical University of Vienna Vienna Austria
DISCo Università Degli Studi di Milano Bicocca Milan Italy
Faculty of Medicine Department of Medical Biochemistry Manisa Celal Bayar University Manisa Türkiye
HMU Health and Medical University GmbH Potsdam Germany
IRCCS Ospedale Galeazzi Sant'Ambrogio Milan Italy
Laboratory Medicine Department Virgen Macarena University Hospital Seville Spain
Laboratory Medicine IRCCS San Raffaele Scientific Institute Milan Italy
MDI Limbach Berlin GmbH Berlin Germany
Medical Faculty in Pilsen Charles University Pilsen Czech Republic
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