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|a Artificial intelligence and big data analytics for smart healthcare /
|c edited by Miltiadis D. Lytras, Anna Visvizi, Akila Sarirete, Kwok Tai Chui.
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|a Amsterdam :
|b Academic Press,
|c 2021.
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|a 1 online resource
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|a Next generation technology driven personalized medicine and smart healthcare
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|a Front Cover -- Artificial Intelligence and Big Data Analytics for Smart Healthcare -- Copyright Page -- Dedication -- Contents -- List of contributors -- Preface: artificial intelligence and big data analytics for smart healthcare: a digital transformation of healthcare primer -- Introduction -- Overview -- List of Abstracts -- Chapter 1 Healthcare in the times of artificial intelligence: setting a value-based context -- Chapter 2 High-level strategy for implementing artificial intelligence (AI) at the Saudi Commission for Health Specialties ...
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|a Chapter 3 Big data infrastructure: data mining, text mining, and citation context analysis in scientific literature -- Chapter 4 Place attachment theories: a spatial approach to smart health and healing -- Chapter 5 Utilizing IoT-based sensors and prediction model for health-care monitoring system -- Chapter 6 QoS of mobile cloud computing applications in healthcare -- Chapter 7 Analysis of Parkinson's disease based on mobile application -- Chapter 8 Mobile Partogram-m-Health technology in the promotion of parturient's health in the delivery room
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|a Chapter 9 Self-evaluation mobile application on mild cognitive impairment based on Mini-Mental State Examination with bilin ... -- Chapter 10 Spatiotemporal Big Data-driven vessel traffic risk estimation for promoting maritime healthcare: lessons learnt ... -- Chapter 11 Neurofeedback using video games for attention-deficit/hyperactivity disorder -- Chapter 12 Medical diagnosis in Alzheimer's disease based on supervised and semisupervised learning -- Chapter 13 A support vector machine-based voice disorders detection using human voice signal
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|a Chapter 14 COVID-19 detection from X-ray images using artificial intelligence -- Chapter 15 Empowering the One Health approach and health resilience with digital technologies across OECD countries: the ca ... -- Chapter 16 An overview of artificial intelligence and Big Data Analytics for smart healthcare: requirements, applications ... -- Conclusion -- References -- Acknowledgments -- 1 Healthcare in the times of artificial intelligence: setting a value-based context -- 1.1 Introduction-mapping the current challenges in the health domain -- 1.2 Value-based approach to healthcare
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|a 1.3 Current state of artificial intelligence utilization in the health domain/artificial intelligence metaphors and its con ... -- 1.4 Conclusion -- References -- Further reading -- 2 High-level strategy for implementing artificial intelligence at the Saudi Commission for Health Specialties -- 2.1 Introduction -- 2.2 Literature review -- 2.3 Current state of AI utilization at the SCFHS -- 2.3.1 Matching prospective trainees (residents) to residency training programs -- 2.3.2 Professional accreditation of health-care practitioners
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|a This text serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers.
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|a Artificial intelligence
|x Medical applications.
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|a Big data.
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650 |
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|a Intelligence artificielle en m�edecine.
|0 (CaQQLa)201-0180593
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|a Donn�ees volumineuses.
|0 (CaQQLa)000284673
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|a Artificial intelligence
|x Medical applications
|2 fast
|0 (OCoLC)fst00817267
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|0 (OCoLC)fst01892965
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|a Lytras, Miltiadis D.,
|d 1973-
|e editor.
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700 |
1 |
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|a Visvizi, Anna,
|d 1976-
|e editor.
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700 |
1 |
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|a Sarirete, Akila,
|e editor.
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700 |
1 |
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|a Chui, Kwok Tai,
|e editor.
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776 |
0 |
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|i Print version:
|z 9780128220627
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776 |
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|i Print version:
|z 9780128220603
|z 0128220600
|w (OCoLC)1222803426
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856 |
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0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128220603
|z Texto completo
|