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Interpretable cognitive internet of things for healthcare

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Interpretable cognitive internet of things for healthcareedited by Utku Kose ... [et al.].
其他作者:	Kose, Utku.
出版者:	Cham :Springer International Publishing :2023.
面頁冊數:	xiv, 193 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Internet of things.
電子資源:	https://doi.org/10.1007/978-3-031-08637-3
ISBN:	9783031086373$q(electronic bk.)

Interpretable cognitive internet of things for healthcare
Interpretable cognitive internet of things for healthcare[electronic resource] /edited by Utku Kose ... [et al.]. - Cham :Springer International Publishing :2023. - xiv, 193 p. :ill., digital ;24 cm. - Internet of things, technology, communications and computing,2199-1081. - Internet of things, technology, communications and computing..

Introduction -- Essentials of Cognitive IoT for Healthcare -- Interpretability Problem in IoT for Healthcare -- Transparent and Black-Box IoT Systems for Healthcare -- Evaluation of Cognitive Capabilities of IoT in Healthcare -- Massive Health Data Analytics for Cognitive IoT -- Usability Evaluation of Cognitive IoT for Healthcare -- Hybrid Methods for Interpretable IoT for Healthcare -- Interpretable Cognitive IoT for Pandemics -- Interpretable Cognitive IoT for Cancer -- Interpretable Cognitive IoT for Sustainable Massive Health -- Interpretable Cognitive IoT for Health Robotics -- Interpretable Cognitive IoT for Personal Healthcare -- Wearables in the Context of IoT for Massive Healthcare -- Security for Massive Health Data Used by Cognitive IoT -- Future Insights for Interpretable Cognitive IoT in Healthcare -- Conclusion.

This book presents research on how interpretable cognitive IoT can work to help with the massive amount of data in the healthcare industry. The authors give importance to IoT systems with intense machine learning features; this ensures the scope corresponds to use of cognitive IoT for understanding, reasoning, and learning from medical data. The authors discuss the interpretability of an intelligent system and its trustworthiness as a smart tool in the context of massive healthcare applications. As a whole, book combines three important topics: massive data, cognitive IoT, and interpretability. Topics include health data analytics for cognitive IoT, usability evaluation of cognitive IoT for healthcare, interpretable cognitive IoT for health robotics, and wearables in the context of IoT for healthcare. The book acts as a useful reference work for a wide audience including academicians, scientists, students, and professionals. Presents research and application of cognitive interpretable data for healthcare; Includes both positive outcomes and negative results of ongoing research into IoT and healthcare; Encourages readers to submit their data or open source software, to create a repository for ongoing study.

ISBN: 9783031086373$q(electronic bk.)

Standard No.: 10.1007/978-3-031-08637-3doiSubjects--Topical Terms:

670954
Internet of things.

LC Class. No.: R859.7.A78 / I58 2023

Dewey Class. No.: 610.28546

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505 0 $a Introduction -- Essentials of Cognitive IoT for Healthcare -- Interpretability Problem in IoT for Healthcare -- Transparent and Black-Box IoT Systems for Healthcare -- Evaluation of Cognitive Capabilities of IoT in Healthcare -- Massive Health Data Analytics for Cognitive IoT -- Usability Evaluation of Cognitive IoT for Healthcare -- Hybrid Methods for Interpretable IoT for Healthcare -- Interpretable Cognitive IoT for Pandemics -- Interpretable Cognitive IoT for Cancer -- Interpretable Cognitive IoT for Sustainable Massive Health -- Interpretable Cognitive IoT for Health Robotics -- Interpretable Cognitive IoT for Personal Healthcare -- Wearables in the Context of IoT for Massive Healthcare -- Security for Massive Health Data Used by Cognitive IoT -- Future Insights for Interpretable Cognitive IoT in Healthcare -- Conclusion.
520 $a This book presents research on how interpretable cognitive IoT can work to help with the massive amount of data in the healthcare industry. The authors give importance to IoT systems with intense machine learning features; this ensures the scope corresponds to use of cognitive IoT for understanding, reasoning, and learning from medical data. The authors discuss the interpretability of an intelligent system and its trustworthiness as a smart tool in the context of massive healthcare applications. As a whole, book combines three important topics: massive data, cognitive IoT, and interpretability. Topics include health data analytics for cognitive IoT, usability evaluation of cognitive IoT for healthcare, interpretable cognitive IoT for health robotics, and wearables in the context of IoT for healthcare. The book acts as a useful reference work for a wide audience including academicians, scientists, students, and professionals. Presents research and application of cognitive interpretable data for healthcare; Includes both positive outcomes and negative results of ongoing research into IoT and healthcare; Encourages readers to submit their data or open source software, to create a repository for ongoing study.
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