Artificial Intelligence and Big Data Analytics for Smart Healthcare

Erscheinungsjahr 2021
ISBN: 978-0-12-822060-3
Verlag: William Andrew Publishing

Buch, Englisch, 290 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 590 g

Artificial Intelligence and Big Data Analytics for Smart Healthcare 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.

Zielgruppe

Clinicians, medical doctors, bioinformaticians

Autoren/Hrsg.

Lytras, Miltiadis

Sarirete, Akila

Visvizi, Anna

Chui, Kwok Tai

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Fertigungsindustrie Spitzentechnologiesektor
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Telemedizin, e-Health
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Public Health, Gesundheitsmanagement, Gesundheitsökonomie, Gesundheitspolitik
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Gesundheitswirtschaft
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik

Inhaltsverzeichnis

Section 1: Big data infrastructure, framework and design for smart healthcareSection 2: Signal processing techniques for smart healthcare applicationsSection 3: Business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcareSection 4: Emerging tools and techniques for smart healthcareSection 5: Challenges (e.g. security, privacy, and policy) in big data for smart healthcare. While in existing books, the focus is on limited areas (sections)Section 6: Appendixes

Über Autor(innen)

Visvizi, Anna
Anna Visvizi is an economist and political scientist, editor, and research and political consultant with extensive experience in academia, think tank and government sectors in Europe and the United States. Associate Professor at SGH Warsaw School of Economics, Warsaw, Poland, and Visiting Scholar at Effat University, Jeddah, Saudi Arabia, Professor Visvizi's expertise covers issues pertinent to the intersection of politics, economics, and ICT. This translates in her research and advisory roles in the fields of AI and geopolitics, smart cities and smart villages, knowledge and innovation management, and technology diffusion, especially with regard to the EU and BRI.

Lytras, Miltiadis
Miltiadis D. Lytras is an expert in advanced computer science and management, editor, lecturer, and research consultant, with extensive experience in academia and the business sector in Europe and Asia. Dr. Lytras is a Research Professor at Deree College - The American College of Greece and a Distinguished Scientist at the King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. Dr. Lytras is a world-class expert in the fields of cognitive computing, information systems, technology enabled innovation, social networks, computers in human behavior, and knowledge management. In his work, Dr. Lytras seeks to bring together and exploit synergies among scholars and experts committed to enhancing the quality of education for all.

Chui, Kwok Tai
Dr. Kwok Tai Chui received the B.Eng. degree in electronic and communication engineering - Business Intelligence Minor, with First-class Honor, and PhD degree from City University of Hong Kong in 2013 and 2017 respectively. He was the recipient of 2nd Prize Award (Postgraduate Category) of 2014 IEEE Region 10 Student Paper Contest. Also, he received Best Paper Award in IEEE The International Conference on Consumer Electronics-China, in both 2014 and 2015. He has published more than 30 research publications in edited book, referred international journals, conferences and book chapters. His research interests include wireless communication, pattern recognition, healthcare, machine learning algorithms and optimization. He has served as various editorial positions and guest editors in referred international journals and conferences.

Sarirete, Akila
Dr. Akila Sarirete is Dean of Graduate Studies and Research at Effat University. She received her PhD degree in Computer Science and Knowledge Management. Her main research interests are in artificial intelligence, knowledge management, communities of practice, machine learning, big data, and service-oriented architectures. She presented her research work in several conferences in different countries. Dr. Sarirete has a vast experience in software development industry and software engineering. She is interested in engineering education, innovation, smart cities and villages especially, the human aspect and the collaborative work.