Artificial Intelligence (AI) Applications in Clinical Laboratories: A Narrative Review

Abstract

Artificial intelligence (AI) is rapidly transforming various sectors, with its impact on healthcare, particularly clinical laboratories, becoming increasingly profound. This narrative review explores the diverse applications of AI within clinical laboratory settings, highlighting its potential to enhance efficiency, accuracy, and diagnostic capabilities. The integration of AI technologies, including machine learning and deep learning, promises to revolutionize traditional laboratory workflows, from sample processing and data analysis to diagnostic interpretation and quality control. This paper synthesizes current literature to delineate how AI is being leveraged for automation, advanced diagnostics, predictive analytics, and the management of infectious diseases. Furthermore, it addresses the challenges associated with AI implementation, such as data quality, ethical considerations, and the need for robust validation frameworks. By critically reviewing existing applications and identifying emerging trends, this paper aims to provide a comprehensive overview of AI’s transformative role in modern laboratory medicine. The findings underscore the imperative for continued research and strategic investment to fully harness AI’s potential in improving patient outcomes and optimizing laboratory operations.