Ulapane Nalika (28 results)

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Paperback. Condition: New. This book centres on the topic of digital twins for superior healthcare decision support, as access is enabled to large volumes of multi-dimensional data such as patient's electronic medical records, medical scans, and data. The reader learns about the possibility of a digital representation of analogous clinical cases built from data-driven models to represent and present relevant information and germane knowledge in context.Together with cutting-edge technologies, the authors share the ability of data-driven models to offer more efficient clinical decision support. The authors take a three-prong approach in the study of digital twins, the positive contributions made in other industries, the different types of applications and the numerous benefits offered. Artificial intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL) algorithms, are discussed in the context of digital twins in healthcare applications. By looking at digital twins it is possible to reduce workflow challenges and provide fast and precise diagnosis. This then demonstrates how digital twins therefore support superior clinical decision-making. Importantly, the authors identify critical success issues, including co-design and research, for the design, development, and deployment of suitable digital twins.This book is written for the healthcare audience, professionals, physicians, medical administrators, managers, and IT practitioners. It also serves as a useful reference for senior-level undergraduate students and graduate students in health informatics and public health.…

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paperback. Condition: New.

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Paperback. Condition: Brand New. 138 pages. 9.18x6.12x9.21 inches. In Stock.

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Condition: New. Nilmini Wickramasinghe is the Optus Chair and Professor of Digital Health at La Trobe University. She has been actively researching and teaching within the health informatics/digital health domain. In 2020, she was awarded an Alexander v.

Paperback. Condition: New. This book centres on the topic of digital twins for superior healthcare decision support, as access is enabled to large volumes of multi-dimensional data such as patient's electronic medical records, medical scans, and data. The reader learns about the possibility of a digital representation of analogous clinical cases built from data-driven models to represent and present relevant information and germane knowledge in context.Together with cutting-edge technologies, the authors share the ability of data-driven models to offer more efficient clinical decision support. The authors take a three-prong approach in the study of digital twins, the positive contributions made in other industries, the different types of applications and the numerous benefits offered. Artificial intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL) algorithms, are discussed in the context of digital twins in healthcare applications. By looking at digital twins it is possible to reduce workflow challenges and provide fast and precise diagnosis. This then demonstrates how digital twins therefore support superior clinical decision-making. Importantly, the authors identify critical success issues, including co-design and research, for the design, development, and deployment of suitable digital twins.This book is written for the healthcare audience, professionals, physicians, medical administrators, managers, and IT practitioners. It also serves as a useful reference for senior-level undergraduate students and graduate students in health informatics and public health.…

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Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Hardback. Condition: New.

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Paperback. Condition: New.

Hardback. Condition: New. This book centres on the topic of digital twins for superior healthcare decision support, as access is enabled to large volumes of multi-dimensional data such as patient's electronic medical records, medical scans, and data. The reader learns about the possibility of a digital representation of analogous clinical cases built from data-driven models to represent and present relevant information and germane knowledge in context.Together with cutting-edge technologies, the authors share the ability of data-driven models to offer more efficient clinical decision support. The authors take a three-prong approach in the study of digital twins, the positive contributions made in other industries, the different types of applications and the numerous benefits offered. Artificial intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL) algorithms, are discussed in the context of digital twins in healthcare applications. By looking at digital twins it is possible to reduce workflow challenges and provide fast and precise diagnosis. This then demonstrates how digital twins therefore support superior clinical decision-making. Importantly, the authors identify critical success issues, including co-design and research, for the design, development, and deployment of suitable digital twins.This book is written for the healthcare audience, professionals, physicians, medical administrators, managers, and IT practitioners. It also serves as a useful reference for senior-level undergraduate students and graduate students in health informatics and public health.…

Hardback. Condition: New.

Hardcover. Condition: Brand New. 138 pages. 9.18x6.12x9.45 inches. In Stock.

Hardback. Condition: New. This book centres on the topic of digital twins for superior healthcare decision support, as access is enabled to large volumes of multi-dimensional data such as patient's electronic medical records, medical scans, and data. The reader learns about the possibility of a digital representation of analogous clinical cases built from data-driven models to represent and present relevant information and germane knowledge in context.Together with cutting-edge technologies, the authors share the ability of data-driven models to offer more efficient clinical decision support. The authors take a three-prong approach in the study of digital twins, the positive contributions made in other industries, the different types of applications and the numerous benefits offered. Artificial intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL) algorithms, are discussed in the context of digital twins in healthcare applications. By looking at digital twins it is possible to reduce workflow challenges and provide fast and precise diagnosis. This then demonstrates how digital twins therefore support superior clinical decision-making. Importantly, the authors identify critical success issues, including co-design and research, for the design, development, and deployment of suitable digital twins.This book is written for the healthcare audience, professionals, physicians, medical administrators, managers, and IT practitioners. It also serves as a useful reference for senior-level undergraduate students and graduate students in health informatics and public health.…

Paperback. Condition: Brand New. 138 pages. 9.18x6.12x9.21 inches. In Stock. This item is printed on demand.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In today s evolving digital landscape, health organizations face responsibilities in delivering care while ensuring ethical, transparent, and informed use of technology. Creating responsible inquiring digital health organizations means building systems that prioritize data integrity, patient privacy, equitable access, and continuous learning through critical inquiry. As AI, telemedicine, and digital records reshape healthcare, it is essential for organizations to foster a culture of accountability, where digital tools are integrated, questioned, evaluated, and improved. This approach empowers health professionals to make informed decisions while instilling public trust in a digital healthcare ecosystem. Creating Responsible Inquiring Digital Health Organizations explores how digital health organizations integrate ethical practices, critical thinking, and continuous learning into technology usage. It examines strategies that promote accountability, patient-centered care, and responsible innovation in a digital health environment. This book covers topics such as biology, digital twins, and generative AI, and is a useful resource for engineers, medical and healthcare professionals, academicians, researchers, and scientists.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In today s evolving digital landscape, health organizations face responsibilities in delivering care while ensuring ethical, transparent, and informed use of technology. Creating responsible inquiring digital health organizations means building systems that prioritize data integrity, patient privacy, equitable access, and continuous learning through critical inquiry. As AI, telemedicine, and digital records reshape healthcare, it is essential for organizations to foster a culture of accountability, where digital tools are integrated, questioned, evaluated, and improved. This approach empowers health professionals to make informed decisions while instilling public trust in a digital healthcare ecosystem. Creating Responsible Inquiring Digital Health Organizations explores how digital health organizations integrate ethical practices, critical thinking, and continuous learning into technology usage. It examines strategies that promote accountability, patient-centered care, and responsible innovation in a digital health environment. This book covers topics such as biology, digital twins, and generative AI, and is a useful resource for engineers, medical and healthcare professionals, academicians, researchers, and scientists.…