USE OF ARTIFICIAL INTELLIGENCE IN LABORATORY DIAGNOSIS: A COMPREHENSIVE REVIEW OF PROS AND CONS

Naveen Prabakaran C

Authors

Naveen Prabakaran C Associate Professor of Biochemistry Faculty of International Studies, Asia International University, Bukhara, Uzbekistan drcnpkaran.oxu@gmail.com

Keywords:

Artificial intelligence; Machine learning; Laboratory diagnosis; Digital pathology; Automation bias; Algorithmic bias; Diagnostic accuracy; Clinical validation; Health equity; Regulatory framework

Abstract

The integration of artificial intelligence (AI) into laboratory medicine represents one of the most transformative developments in modern healthcare diagnostics. This review examines the dual nature of AI implementation in laboratory settings, analyzing its substantial benefits alongside significant challenges and risks. While AI offers remarkable potential for enhancing diagnostic accuracy, accelerating turnaround times, and addressing global workforce shortages, it simultaneously presents concerns regarding automation bias, algorithmic bias, regulatory complexities, and the potential erosion of clinical expertise. Drawing on recent literature and emerging trends for 2026, this article provides a balanced perspective on how laboratories can harness AI’s capabilities while mitigating its inherent risks through thoughtful implementation, continuous education, and robust oversight frameworks.

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