This title offers a reference for readers hoping to combine computer vision and machine learning. Contributors offer diverse perspectives drawn from an international pool. The book shows the development of algorithms and architectures for healthcare. Explainable AI opens ML up to show the reasons behind the decisions taken by automated algorithms, bridging a gap in meaning between those designing the technology and those implementing it in healthcare. Three sections present the role of computer vision and ML for preprocessing, application of ML to diseases and the role of explainability and interoperability of ML in healthcare. This book will be a valuable reference to medical practitioners, researchers and students interested in understanding and applying computer vision and ML in the healthcare sector.
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