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Explainable AI in Healthcare
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Explainable AI in Healthcare : Unboxing Machine Learning for Biomedicine

Book Details

Format Hardback or Cased Book
ISBN-10 1032367113
ISBN-13 9781032367118
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Jul 17th, 2023
Print length 304 Pages
Weight 620 grams
Dimensions 16.20 x 24.20 x 2.40 cms
Ksh 18,900.00
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This title covers computer vision and machine learning (ML) advances that facilitate automation in diagnostic, therapeutic, and preventative healthcare. The book shows the development of algorithms and architectures for healthcare.

This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering.

This book will benefit readers in the following ways:

  • Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care
  • Investigates bridges between computer scientists and physicians being built with XAI
  • Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent
  • Initiates discussions on human-AI relationships in health care
  • Unites learning for privacy preservation in health care

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