Artificial Intelligence and Digital Pathology in Hematological Diagnostics

This chapter examines the transformative integration of artificial intelligence (AI), machine learning, and digital pathology platforms into the diagnostic workflow of hematological diseases, from automated morphological analysis of peripheral blood smears and bone marrow aspirates to AI-driven interpretation of flow cytometry and genomic data. It reviews the current state of deep learning algorithms validated for blood cell classification and hematological malignancy detection, and discusses their performance benchmarks relative to expert human analysis. The chapter also addresses critical considerations of algorithmic bias, regulatory frameworks for AI-based medical devices, clinical implementation challenges, and the broader implications of digital transformation for hematology laboratory practice globally.