Digital Twins: For Superior Clinical Decision Making
暫譯: 數位雙胞胎：提升臨床決策的優越性
Wickramasinghe, Nilmini, Ulapane, Nalika, Andargoli, Amir
- 出版商: CRC
- 出版日期: 2025-08-22
- 售價: $6,400
- 貴賓價: 9.5 折 $6,080
- 語言: 英文
- 頁數: 134
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1032780355
- ISBN-13: 9781032780351
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相關分類:
人工智慧、Data Science
海外代購書籍(需單獨結帳)
相關主題
商品描述
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, 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 how digital twins reduce workflow challenges, provide fast and precise diagnosis, therefore support superior clinical decision making. Importantly, the editors 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 the IT practitioner. It would also serve as a useful reference for the senior level undergraduate students and graduate students in health informatics and public health.
商品描述(中文翻譯)
這本書的主題圍繞數位雙胞胎在優質醫療決策支持中的應用，因為可以訪問大量的多維數據，例如病人的電子病歷、醫療掃描和數據。讀者將了解如何利用數據驅動模型構建類似臨床案例的數位表示，以在上下文中呈現相關信息和相關知識的可能性。
結合尖端技術，作者分享了數據驅動模型提供更高效臨床決策支持的能力。作者在數位雙胞胎的研究中採取了三個方面的探討，包括其他行業的正面貢獻、不同類型的應用以及所提供的眾多好處。書中討論了人工智慧（AI）技術，如機器學習（ML）和深度學習（DL）算法在醫療應用中數位雙胞胎的背景。通過觀察數位雙胞胎如何減少工作流程挑戰、提供快速且精確的診斷，從而支持優質的臨床決策。重要的是，編輯們確定了關鍵成功問題，包括共同設計和研究，以設計、開發和部署合適的數位雙胞胎。
這本書是為醫療領域的讀者撰寫的，包括專業人士、醫生、醫療管理人員、經理和IT從業者。它也將作為健康資訊學和公共衛生領域的高年級本科生和研究生的有用參考資料。
作者簡介
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 von Humboldt award for her outstanding contribution to digital health.
Nalika Ulapane is a researcher contributing to the design, development, and assessment of digital health solutions. He brings mathematical modelling, engineering systems design, and design science research principles to solve problems in complex systems like the healthcare sector.
Amir Andargoli focuses primarily on digitalization and digital transformation within the healthcare sector. He draws upon principles from information systems and management to conduct his research, which has resulted in publications in peer-reviewed journals and international symposiums.
作者簡介(中文翻譯)
Nilmini Wickramasinghe 是拉籌伯大學的 Optus 教授及數位健康教授。她在健康資訊學/數位健康領域積極從事研究和教學。2020 年，她因對數位健康的卓越貢獻而獲得亞歷山大·馮·洪堡獎。
Nalika Ulapane 是一位研究人員，致力於數位健康解決方案的設計、開發和評估。他運用數學建模、工程系統設計和設計科學研究原則來解決像醫療保健行業這樣的複雜系統中的問題。
Amir Andargoli 主要專注於醫療保健行業的數位化和數位轉型。他借鑒資訊系統和管理的原則進行研究，並在同行評審的期刊和國際研討會上發表了多篇論文。
