Morphological Diagnosis in Hematology

Morphological changes in erythrocytes provide important diagnostic clues that can facilitate the timely diagnosis and appropriate management of affected individuals. Furthermore, specific laboratory and diagnostic tests can be used to confirm the underlying disorder. The advent of machine learning and artificial intelligence has further accelerated and enhanced this diagnostic process by enabling the automated analysis of erythrocyte morphological features. This book integrates traditional microscopic assessment of erythrocyte morphology with emerging applications of machine learning and artificial intelligence, providing readers with a comprehensive and more precise approach to the diagnosis of erythrocyte disorders.