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Explainable AI in Healthcare

- Unboxing Machine Learning for Biomedicine
Engelsk Hardback

Explainable AI in Healthcare

- Unboxing Machine Learning for Biomedicine
Engelsk Hardback
Tjek vores konkurrenters priser

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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Tjek vores konkurrenters priser
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Tjek vores konkurrenters priser

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
Vis mere
Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 304
ISBN-13: 9781032367118
Indbinding: Hardback
Udgave:
ISBN-10: 1032367113
Kategori: Medicinsk & sundhedsfaglig informatik
Udg. Dato: 17 jul 2023
Længde: 24mm
Bredde: 242mm
Højde: 162mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 17 jul 2023
Forfatter(e):
Forfatter(e)

Kategori Medicinsk & sundhedsfaglig informatik

ISBN-13 9781032367118

Sprog Engelsk

Indbinding Hardback

Sider 304

Udgave

Længde 24mm

Bredde 242mm

Højde 162mm

Udg. Dato 17 jul 2023

Oplagsdato 17 jul 2023

Forlag Taylor & Francis Ltd