EVOLVING TRENDS IN DIAGNOSTIC PATHOLOGY: FROM CONVENTIONAL MICROSCOPY TO DIGITAL AND AI-ASSISTED SYSTEMS – A NARRATIVE REVIEW

Abstract

Background: The field of diagnostic pathology is undergoing a paradigm shift from traditional light microscopy toward digitally enhanced and artificial intelligence (AI)-assisted systems. This transition is driven by growing demands for diagnostic accuracy, efficiency, and accessibility amid rising global disease burdens and workforce shortages. Digital pathology and AI applications are increasingly being integrated into clinical, educational, and research settings, presenting both opportunities and challenges for contemporary pathology practice.

Objective: This narrative review aims to explore the evolving landscape of diagnostic pathology, focusing on the transition from conventional microscopy to digital platforms and AI-supported systems. The review highlights current developments, assesses their implications, and identifies gaps in the literature to inform future research and clinical implementation.

Main Discussion Points: Key themes include the adoption of whole slide imaging (WSI), the role of AI in augmenting diagnostic accuracy and workflow efficiency, and the use of digital pathology in education and infectious disease diagnosis. The review also addresses critical limitations in current research, including methodological inconsistencies, limited generalizability, and publication bias. Interoperability issues and the need for standardized guidelines are discussed as major hurdles to widespread adoption.

Conclusion: Digital and AI-assisted pathology systems hold substantial promise for improving diagnostic practice, yet robust clinical validation remains limited. There is a clear need for large-scale, methodologically sound studies to guide evidence-based integration. Strategic implementation and ongoing research are essential to harness the full potential of these innovations in routine pathology.