Morphological Diagnosis in Hematology
Clinical Case Studies – From Microscope to Machine Learning Validation
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Beschreibung
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.
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.
Bridges the critical gap between traditional microscopy expertise and AI-driven diagnostics in hematopathology Features practical implementation frameworks for integrating machine learning into routine laboratory workflows Includes annotated image libraries that serve as both diagnostic references and AI training resources
Autor*in
Akbar Dorgalaleh
Themen in »Morphological Diagnosis in Hematology«
Hematological Image Analysis Digital Hematopathology AI-assisted Blood Cell Morphology Analysis Machine Learning Anemia Diagnosis AI Hematology Diagnostics Digital Microscopy Blood Cells Deep Learning Blood Cell Identification