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Titlebook: Internet of Medical Things for Smart Healthcare; Covid-19 Pandemic Chinmay Chakraborty,Amit Banerjee,Joel J. P. C. Ro Book 2020 The Editor(

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發(fā)表于 2025-3-21 19:12:45 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Internet of Medical Things for Smart Healthcare
副標題Covid-19 Pandemic
編輯Chinmay Chakraborty,Amit Banerjee,Joel J. P. C. Ro
視頻videohttp://file.papertrans.cn/473/472448/472448.mp4
概述Covers comprehensive studies from bioelectronics and biomedical engineering with a prime focus on COVID-19 pandemic.Proposes effective protocols using the intelligence gained via data.Focuses on recen
叢書名稱Studies in Big Data
圖書封面Titlebook: Internet of Medical Things for Smart Healthcare; Covid-19 Pandemic Chinmay Chakraborty,Amit Banerjee,Joel J. P. C. Ro Book 2020 The Editor(
描述This book?covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies. It includes reviews and original works on COVID-19 in terms of e-healthcare, medicine technology, life support systems, fast detection,?diagnoses, developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, solutions for monitoring and control of the spread of COVID-19, among other topics. The book covers comprehensive studies from bioelectronics and biomedical engineering, artificial intelligence, and big data with a prime focus on COVID-19 pandemic..
出版日期Book 2020
關鍵詞Smart Healthcare; COVID-19 Pandemic; Biomedical Image Processing; Health Informatics; IoT Applications; H
版次1
doihttps://doi.org/10.1007/978-981-15-8097-0
isbn_softcover978-981-15-8099-4
isbn_ebook978-981-15-8097-0Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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2197-6503 cols using the intelligence gained via data.Focuses on recenThis book?covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies. It includes reviews and original works on COVID-19 in terms of e-healthcare, medicine technolo
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2197-6503 lutions for monitoring and control of the spread of COVID-19, among other topics. The book covers comprehensive studies from bioelectronics and biomedical engineering, artificial intelligence, and big data with a prime focus on COVID-19 pandemic..978-981-15-8099-4978-981-15-8097-0Series ISSN 2197-6503 Series E-ISSN 2197-6511
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Diagnosing COVID-19 Lung Inflammation Using Machine Learning Algorithms: A Comparative Study,mages using morphological approaches. In the second phase, we use machine learning algorithms to classify the pneumonia level of the confirmed COVID-19 patient. Extensive experiments have been carried out and the results show the accuracy of 91.304%, 91.4%, 87.5%, 95.622% for kNN, SVM, DT, and CNN, respectively.
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Factors Affecting the Success of Internet of Things for Enhancing Quality and Efficiency Implementaon technology sector. This is done through improving healthcare delivery by increasing efficiency, reducing cost and time involved. However, the applicability of DeLone and McLean?IS success model achievement model for health welfare implementation in IoT remains unknown. Thus, this research amid to
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