Artificial Intelligence in Clinical Laboratories: A Bibliometric Analysis of Research Trends and Applications

Abstract

The progress of artificial intelligence (AI) has rapidly increased its use in clinical laboratories, making it easier to diagnose patients and run the laboratories more efficiently. Nonetheless, difficulties remain regarding the ethical aspects, uniformity, and reliability of algorithmic decision-making. This study seeks to delineate the evolution of AI applications in clinical laboratories over the preceding five years through a bibliometric analysis. We obtained original articles from the Scopus database published between 2021 and 2025 in the fields of medicine, computer science, and health professions. A systematic identification and screening process resulted in 1,891 documents, followed by filtering, duplicate removal, and eligibility assessment, giving in the inclusion of 994 studies in the final analysis. We conducted a bibliometric analysis to examine publication trends, changes in themes over time, co-occurrence of keywords, networks of international collaboration, and highly cited core studies. The results show that research output is growing quickly, and the focus is shifting from developing new methods to putting them into practice in the real world. Keyword mapping indicates that automation, diagnostic accuracy, and decision-support systems are becoming increasingly important. International collaboration is growing, but it is still unevenly distributed across regions. In conclusion, this study offers a thorough examination of the evolving research landscape of AI in clinical laboratories and underscores the need for enhanced global collaboration and the ethical, clinically reliable, and sustainable incorporation of AI in clinical laboratories.