Internet of Things enabled Machine Learning for Biomedical Applications (eBook, ePUB)

Redaktion: Goel, Neha; Yadav, Ravindra Kumar

• Format: ePub

Produktbeschreibung

The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things.

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Produktdetails

• Verlag: Taylor & Francis
• Erscheinungstermin: 29. November 2024
• Englisch
• ISBN-13: 9781040097663
• Artikelnr.: 72247485

Autorenporträt

Dr. Neha Goel is working as Professor in the Department of Electronics & Communication Engineering, RKGIT, Ghaziabad, India. She has Ph.D. degree from SRM University, Chennai, in 2019. She has 18 years of rich experience in teaching and research and development activities. Her area of interest is VLSI design, CMOS design, Internet of Things, and machine learning. She has guided several B.Tech and M.Tech Projects and has published 45 papers in various national/ international journals and conferences. She has received many grants and has published Four patents. She has also attended various workshops and seminars in various fields. Dr. Ravindra Kumar Yadav is Professor and Head of the Department of Electronics & Communication Engineering, RKGIT, Ghaziabad, India. He has B.E., M.E., and Ph.D. degrees in the field of Electronics & Communication Engineering. He has 26 years of rich experience in teaching, research and development activities, administration and managing, and establishing higher educational institutions. He has guided several B. Tech. and M.Tech. projects and is also guiding Ph.D. students from IIT Dhanbad as a co-guide. He has 90 papers to his credit, published in international/national journals, conferences, and symposiums. Prof. Yadav is reviewer for several national/international journals of high repute. He has chaired/participated in technical sessions at multiple international and national conferences/seminars held throughout the country.

Inhaltsangabe

1. ML and IoT coupled Bio-Medical applications in Healthcare: Smart Growth
and Upcoming Challenges. 2. Recent Advances in Ubiquitous Sustainable
Healthcare Systems. 3. IoT enabled Healthcare System using Machine
Learning. 4. An Efficient Architecture for Classification of Super
Resolution Enhanced Human Chromosome Images. 5. Applications of Machine
Learning to the Impact of IoT in Biomedical Applications. 6. Ovarian Cancer
Detection Using IoT-Based Intelligent Assistant and Blockchain Technology.
7. Blood oxygen level and pulse rate measurement using hemodialysis using
IoT and Computational Intelligence. 8. Dental Shade Matching using machine
Learning Models. 9. Brain Tumor Detection for Recognising Critical Brain
Damage in Patients Using Computer Vision. 10. Smart Therapist: The Mental
Health detector. 11. Medical Image Analysis based on Deep Learning Approach
and Internet of Medical Things (IoMT) for early Diagnosis of Retinal
disease. 12. Intelligent E-Learning Platform Consolidating Web of Things
and Chat-GPT. 13. Issues and Challenges in security and privacy with
E-health care: a thorough literature analysis. 14. Harnessing the Power of
Distributed Cloud and Edge Computing for Advanced Healthcare Systems. 15.
Securing Cloud-Based IoT: Exploring the Significance of Lightweight
Cryptography for Enhanced Security. 16. Security and Privacy in the
Internet of Medical Things (IoMT)-Based Healthcare: Ensuring Trust and
Safety. 17. A Comprehensive Study of the Problem and Challenges Associated
with Machine Learning Enabled IOT in Biomedical Applications. 18. A Machine
Learning-enabled Internet of Things Model for Cloud-based Biomedical
Applications. 19. Machine Learning Enabled IoT for Biomedical applications:
Problem and challenges. 20. IOT driven Machine learning mechanisms for
Healthcare Applications.