Digital twin technologies for healthcare 4.0

In healthcare, a digital twin is a digital representation of a patient or healthcare system using integrated simulations and service data. The digital twin tracks a patient's records, crosschecks them against registered patterns and analyses any diseases or contra indications. The digital twin...

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Bibliographic Details
Other Authors: Dhanaraj, Rajesh Kumar, (Editor), Murugesan, Santhiya, (Editor), Balusamy, Balamurugan, (Editor), Balas, Valentina Emilia, (Editor)
Format: eBook
Language: English
Published: Hertfordshire, United Kingdom : Institution of Engineering & Technology, 2022.
Series: Healthcare technologies series ; 46.
Subjects:
ISBN: 1839535806
9781839535802
1839535792
9781839535796
Physical Description: 1 online resource (xii, pages).

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Summary: In healthcare, a digital twin is a digital representation of a patient or healthcare system using integrated simulations and service data. The digital twin tracks a patient's records, crosschecks them against registered patterns and analyses any diseases or contra indications. The digital twin uses adaptive analytics and algorithms to produce accurate prognoses and suggest appropriate interventions. A digital twin can run various medical scenarios before treatment is initiated on the patient, thus increasing patient safety as well as providing the most appropriate treatments to meet the patient's requirements. <italic>Digital Twin Technologies for Healthcare 4.0</italic> discusses how the concept of the digital twin can be merged with other technologies, such as artificial intelligence (AI), machine learning (ML), big data analytics, IoT and cloud data management, for the improvement of healthcare systems and processes. The book also focuses on the various research perspectives and challenges in implementation of digital twin technology in terms of data analysis, cloud management and data privacy issues. With chapters on visualisation techniques, prognostics and health management, this book is a must-have for researchers, engineers and IT professionals in healthcare as well as those involved in using digital twin technology, AI, IoT and big data analytics for novel applications.
Bibliography: Includes bibliographical references and index
ISBN: 1839535806
9781839535802
1839535792
9781839535796
Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty