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Digital Transformation in Healthcare 5.0

- Volume 1: Iot, AI and Digital Twin

Bag om Digital Transformation in Healthcare 5.0

"Digital Transformation in Healthcare 5.0: IoT, AI, and Digital Twin" provides a comprehensive overview of the integration of cutting-edge technology with healthcare, from the Fourth Industrial Revolution (4IR) to the introduction of IoT, AI, and Digital Twin technologies. This in-depth discussion of the digital revolution expanding the healthcare industry covers a wide range of topics, including digital disruption in healthcare delivery, the impact of 4IR and Health 4.0, e-health services and applications, virtual reality's impact on accessible healthcare delivery, digital twins and dietary health technologies, big data analytics in healthcare systems, machine learning models for cost-effective healthcare delivery systems, affordable healthcare with machine learning, enhanced biomedical signal processing with machine learning, and data-driven AI for information retrieval of biomedical images.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783111326467
  • Indbinding:
  • Hardback
  • Udgivet:
  • 6. maj 2024
  • Størrelse:
  • 170x244x21 mm.
  • Vægt:
  • 757 g.
  Gratis fragt
Leveringstid: 8-11 hverdage
Forventet levering: 16. december 2024
Forlænget returret til d. 31. januar 2025

Beskrivelse af Digital Transformation in Healthcare 5.0

"Digital Transformation in Healthcare 5.0: IoT, AI, and Digital Twin" provides a comprehensive overview of the integration of cutting-edge technology with healthcare, from the Fourth Industrial Revolution (4IR) to the introduction of IoT, AI, and Digital Twin technologies. This in-depth discussion of the digital revolution expanding the healthcare industry covers a wide range of topics, including digital disruption in healthcare delivery, the impact of 4IR and Health 4.0, e-health services and applications, virtual reality's impact on accessible healthcare delivery, digital twins and dietary health technologies, big data analytics in healthcare systems, machine learning models for cost-effective healthcare delivery systems, affordable healthcare with machine learning, enhanced biomedical signal processing with machine learning, and data-driven AI for information retrieval of biomedical images.

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