Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Laboratory Professionals' Perspectives on Artificial Intelligence in Laboratory Medicine: Insights from a National Survey in Albania.
0
Zitationen
9
Autoren
2026
Jahr
Abstract
Introduction: While Artificial Intelligence (AI) is transforming Laboratory Medicine, successful AI integration depends on the readiness of healthcare professionals. This study aimed to assess the perspectives of Albanian laboratory professionals toward AI integration in medical laboratories. Methods: We conducted a cross-sectional, voluntary, and anonymous survey using Google Forms. The survey link was distributed to all members of the Albanian Society of Clinical Biochemistry and Laboratory Medicine and their affiliated staff. The survey explored General Information and Demographics, Digital Properties and Health Data Access, and Perspectives on Artificial Intelligence in Medical Laboratories. Responses were automatically collected over four weeks and were analyzed to investigate laboratory professionals' perspectives. Results: A total of 220 laboratory professionals completed the survey. 30% of participants were laboratory doctors and 70% were laboratory technicians. Participants expressed a generally optimistic outlook on AI integration in medical laboratories, believing it could streamline routine workflows and save time (74%), simplify repetitive tasks (70%), reduce work-related stress (61%), improve analytical accuracy and precision (57%), and reduce costs and enhance efficiency (49%). The main barriers to AI integration were considered high cost of implementation, the lack of appropriate IT infrastructure, the lack of specialized staff, and ethical considerations. Significant differences were observed among various subgroups, but interest in AI training prevailed among the majority of respondents. Conclusion: This survey highlights a generally positive perspective on AI among laboratory professionals in Albania, alongside a strong interest in AI education. According to the survey respondents, strengthening digital infrastructure and promoting training programs will be essential for AI integration in laboratory medicine.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.560 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.451 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.948 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.797 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.