Machine Learning for Critical Internet of Medical Things
Springer International Publishing (Verlag)
978-3-030-80930-0 (ISBN)
- Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas;
- Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer;
- Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.
Prof. Dr. Fadi Al-Turjman received his Ph.D. in computer science from Queen's University, Kingston, Ontario, Canada, in 2011. He is a full professor and a research center director at Near East University, Nicosia, Cyprus. Prof. Al-Turjman is a leading authority in the areas of smart/intelligent, wireless, and mobile networks' architectures, protocols, deployments, Multimedia analysis and performance evaluation. His publication history spans over 250 publications in journals, conferences, patents, books, and book chapters, in addition to numerous keynotes and plenary talks at flagship venues. He has authored and edited more than 25 books about cognition, security, and wireless sensor networks' deployments in smart environments, published by Taylor and Francis, Elsevier, and Springer. He has received several recognitions and best papers' awards at top international conferences. He also received the prestigious Best Research Paper Award from Elsevier Computer Communications Journal for the period 2015-2018, in addition to the Top ResearcherAward for 2018 at Antalya Bilim University, Turkey. Prof. Al-Turjman has led a number of international symposia and workshops in flagship communication society conferences. Currently, he serves as an associate editor and the lead guest/associate editorfor several well reputed journals, including the IEEE Communications Surveys and Tutorials(IF 22.9)and the Elsevier Sustainable Cities and Society(IF 4.7).
Anand Nayyar (Senior Member, IEEE) received the Ph.D. degree in computer science from Desh Bhagat University, in 2017, in the area of wireless sensor networks. He is currently working with the Graduate School, Duy Tan University, Da Nang, Vietnam. He is also a Certified Professional with more than 75 professional certificates from CISCO, Microsoft, Oracle, Google, Beingcert, EXIN, GAQM, Cyberoam, and many more. He has published more than 300 research articles in various National and International Conferences, and International Journals (Scopus/SCI/SCIE/SSCI Indexed). He is also a member of more than 50 Associations as a Senior Member and a Life Member and also acting as an ACM Distinguished Speaker. He has authored/coauthored cum Edited 25 Books of computer science. He has associated with more than 400 International Conferences as programme committee/advisory board/review board member. He has two patents to his name in the area of Internet of Things and speech processing. He is currently working in the area of wireless sensor networks, MANETS, swarm intelligence, cloud computing, Internet of Things, Blockchain, machine learning, deep learning, cyber security, network simulation, and wireless communications. He has awarded more than 20 Awards for Teaching and Research-Young Scientist, the Best Scientist, the Young Researcher Award, the Outstanding Researcher Award, the Indo-International Emerging Star Award (to name a few). He is acting as the Editor in Chief of IGI-Global, USA journal titled International Journal of Smart Vehicles and Smart Transportation (IJSVST).
Introduction.- An Introduction to Basic Concepts on Machine Learning, its architecture and framework.- Machine Learning Models and techniques.- Diseases diagnosis and prediction using Machine Learning.- Machine learning for Mobile/e-health, Tele-medical and Remote healthcare networks.- Machine learning in biomedical, Neuro-critical and medical image processing field.- AI, Deep learning and machine learning enabled connected health informatics.- Machine learning enabled smart healthcare system.- Machine learning based efficient health monitoring systems.- Machine learning case study for virus disease Ebola, COVID-19 consequences.- CASE Study: Machine Learning in Medical domain for Cervical Cancer.- Use cases and applications of machine learning in medical domain.- Conclusion.
| Erscheinungsdatum | 06.02.2023 |
|---|---|
| Zusatzinfo | X, 261 p. 89 illus., 79 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 421 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| Schlagworte | AI Internet of Medical Things • Deep Learning and Internet of Medical Things • Image Processing and Internet of Medical Things • Machine Learning and Cervical Cancer • Machine Learning and COVID-19 • Machine Learning and Ebola • Machine Learning and Internet of Medical Things • Viruses and Internet of Medical Things |
| ISBN-10 | 3-030-80930-7 / 3030809307 |
| ISBN-13 | 978-3-030-80930-0 / 9783030809300 |
| Zustand | Neuware |
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