Computational Intelligence for Medical Internet of Things (MIoT) Applications

Machine Intelligence Applications for IoT in Healthcare
Erscheinungsjahr 2023
ISBN: 978-0-323-99421-7
Verlag: Elsevier Science & Technology

Buch, Englisch, 358 Seiten, Format (B × H): 193 mm x 235 mm, Gewicht: 792 g

Computational Intelligence for Medical Internet of Things (MIoT) Applications: Machine Intelligence Applications for IoT in Healthcare explores machine intelligence techniques necessary for effective MIoT research and practice, taking a practical approach for practitioners and students entering the field. This book investigates advanced concepts and applications in the MIoT field, guiding readers through emerging developments and future trends. A wide range of international authors guide readers through advanced concepts, including deep learning, neural network, and big data analytic approaches for the classification, indexing, retrieval, analysis, and inferencing of healthcare data.

Zielgruppe

<p>Biomedical Engineers, Data Analysts, Researchers, Master and PhD students</p> <p>Healthcare Professionals</p>

Autoren/Hrsg.

El-Latif, Ahmed A. Abd

Maleh, Yassine

Curran, Kevin

Siarry, Patrick

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik

Inhaltsverzeichnis

SECTION 1 Computational Intelligence for Medical Internet of Things (MIoT): Current states and Challenges

1. AI and IoT working for healthcare: general aspects and application examples

2. AIoMT Artificial Intelligence (AI) and Internet of Medical Things (IoMT): Applications, Challenges, and Future Trends

3. Artificial Intelligence in Healthcare: Current Situation and Future Possibilities

4. Exploring the effectiveness of cloud, Internet of Things and fog computing for healthcare monitoring systems

5. Patients Using Real-Time remote Health Monitoring Applications: A review

SECTION 2 Computational Intelligence for Medical Internet of Things (MIoT): Applications

6. A Review on The Application of The Internet of Things in Monitoring Autism and Assisting Parents and Caregivers

7. Regression Analysis of the Most Frequent Medical Diagnosis in a Mediterranean Country

8. A conceptual framework for Artificial Intelligence of Medical Things (AIoMT)

9. Framework for integrating healthcare Big Data using IoMT technology

10. Application of computational intelligence in visual optimization tools to improve the performance of medical MIoT platforms

SECTION 3 Computational Intelligence for Medical Internet of Things (MIoT): Security and Privacy

11. Edge Intelligence Case Study on Medical Internet of Things Security

12. Data-driven Intelligent Medical Internet of Things (MIoT) Based Healthcare Solutions for Secured Smart Cities

13. A Secure and Efficient Two-factor Authentication Protocol for Body Sensor Networks

14. Pervasive M-health for Chronic Diseases

15. Hybrid Intelligence Based Cryptosystem: Security and Privacy Enhancement in Telemedicine System

Über Autor(innen)

Siarry, Patrick
Patrick Siarry was born in France in 1952. He received the Ph.D. degree in computer science and optimization from University Paris VI, Paris, France, in 1986, and the Doctorate of Sciences (Habilitation) degree in computer science and optimization from University Paris XI, Orsay, France, in 1994.,He was first involved in the development of analog and digital models of nuclear power plants with Electricité de France, Paris. Since 1995, he has been a Professor of Automatics and Informatics with Université Paris-Est Créteil, Créteil, France. His main research interests include computer-aided design of electronic circuits, cognitive intelligence, and the applications of new stochastic global optimization heuristics to various engineering fields, also including the fitting of process models to experimental data, the learning of fuzzy rule bases, and of neural networks.

El-Latif, Ahmed A. Abd
Prof. Ahmed Abd El-Latif: (B.Sc. with honor rank in Mathematics and Computer Science in 2005, (M.Sc in Computer Science in 2010), and Ph. D. in Computer Science & Technology at Harbin Institute of Technology, Harbin, P. R. China in 2013. He is an associate professor of Computer Science at Menoufia University, Egypt and School of Information Technology and Computer Science, Nile University, Egypt. He is author and co-author of more than indexed 140 papers. He is a referee of many referred international repute journals and conferences. He received many awards, State Encouragement Award in Engineering Sciences 2016, Arab Republic of Egypt; the best Ph.D. student award from Harbin Institute of Technology, China 2013; Young scientific award, Menoufia University, Egypt 2014. He is a fellow at Academy of Scientific Research and Technology, Egypt. Dr. Abd El-Latif is an associate editor in several Scopus Journals and leading many Special issues in SCI journals.

Maleh, Yassine
Prof. Yassine Maleh is a cybersecurity professor and practitioner with industry and academic experience. He is a Ph.D. degree in Computer Sciences. Since 2019, He working as a professor of cybersecurity at Sultan Moulay Slimane University, Morocco. He worked for the National Port agency (ANP) in Morocco as a Senior Security Analyst from 2012 to 2019. He is a senior member of IEEE, a member of the International Association of Engineers and the Machine Intelligence Research Labs. Dr. Maleh has made contributions in information security and privacy, Internet of Things security, and wireless and constrained network security. His research interests include information security and privacy, Internet of Things, networks security, information system and IT governance. He has published over 60 papers (book chapters, international journals, conferences/workshops), 10 edited books, and 3 authored books. He is the editor-in-chief of the International Journal of Smart Security Technologies. He serves as an associate editor for IEEE Access (2019 Impact Factor 4.098), the International Journal of Digital Crime and Forensics, and the International Journal of Information Security and Privacy. He was also a guest editor of a special issue on 'Recent Advances on Cyber Security and Privacy for Cloud-of-Things' of the International Journal of Digital Crime and Forensics, Volume 10, Issue 3, July-September 2019.

Curran, Kevin
Prof. Kevin Curran is a Professor of Cyber Security, Executive Co-Director of the Legal innovation Centre and group leader of the Ambient Intelligence & Web Technologies Research Group at Ulster University. He is also a senior member of the IEEE. Prof Curran is globally recognized as a security Top Influencer "IFSEC Global influencers in security and fire 2020" in category Security thought leadership. He was ranked #2.
Prof Curran is perhaps most well-known for his work on Internet security & location positioning evidenced by over 800 published works. His expertise has been acknowledged by invitations to present his work at international conferences, overseas universities and research laboratories. He is a regular contributor on TV & radio and in trade and consumer IT magazines with 1000+ interviews in recent years. He is currently the recipient of a Royal Academy of Engineering Senior Research Fellowship and is an IEEE Technical Expert for Internet Security. Professor Curran has performed external panel duties for various Higher Education Institutions and public bodies such as OFCOM and the National Institute for Health Research (NIHR).