Morphological Diagnosis in Hematology: Clinical Case Studies - From Microscope to Machine Learning Validation

This book presents a unique collection of carefully selected clinical case studies that bridge classical morphological examination with the power of artificial intelligence in diagnostic hematology. Each case guides the reader through the systematic microscopic analysis of blood or bone marrow specimens, followed by machine learning application, demonstrating how human expertise and ML work in synergy to enhance diagnostic accuracy. Written for hematologists, pathologists, medical technologists, and trainees, this volume serves as both a practical reference and an inspiring insight into the future of AI-assisted hematological diagnosis.