Transforming Clinical Laboratories Through Artificial Intelligence and Automation: A Comprehensive Review
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Abstract
Background: Clinical laboratories are experiencing rapid transformation due to advances in artificial intelligence (AI) and automation, creating new opportunities to improve diagnostic quality, laboratory efficiency, and patient care.
Objective: This review examines current applications of AI and automation in clinical laboratories, highlighting their impact on laboratory workflows, diagnostic performance, operational efficiency, and healthcare delivery.
Methods: Relevant literature published between 2018 and 2026 was reviewed using major scientific databases, including PubMed, Scopus, Web of Science, and IEEE Xplore. Studies addressing AI technologies, laboratory automation, digital pathology, laboratory information systems, and quality improvement were included.
Results: The evidence indicates that AI and automation contribute to faster turnaround times, improved diagnostic accuracy, reduced human error, optimized resource utilization, and enhanced decision-making. Despite these benefits, challenges related to data quality, regulatory compliance, implementation costs, cybersecurity, and workforce readiness continue to influence successful adoption.
Conclusion: AI and automation are reshaping clinical laboratory practice. Continued investment in infrastructure, governance, and workforce development will be essential to support the development of intelligent, reliable, and patient-centered laboratory services.