Internet of Things enabled Machine Learning for Biomedical Applications
portes grátis
Internet of Things enabled Machine Learning for Biomedical Applications
Goel, Neha; Yadav, Ravindra Kumar
Taylor & Francis Ltd
11/2024
410
Dura
9781032550824
Pré-lançamento - envio 15 a 20 dias após a sua edição
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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.
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Image Processing;Image Segmentation;Face Recognition;Health Monitoring System;Computational Intelligence;Security and Privacy
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
