Buch, Englisch, 356 Seiten, Format (B × H): 155 mm x 236 mm, Gewicht: 1111 g
Advances, Challenges and Applications
Buch, Englisch, 356 Seiten, Format (B × H): 155 mm x 236 mm, Gewicht: 1111 g
ISBN: 978-1-138-49247-9
Verlag: Taylor & Francis Ltd (Sales)
Key Features:
- Addresses various applications of Medical Big Data and Internet of Medical Things in real time environment
- Highlights recent innovations, designs, developments and topics of interest in machine learning techniques for classification of medical data
- Provides background and solutions to existing challenges in Medical Big Data and Internet of Medical Things
- Provides optimization techniques and programming models to parallelize the computationally intensive tasks in data mining of medical data
- Discusses interactions, advantages, limitations, challenges and future perspectives of IoT based remote healthcare monitoring systems.
- Includes data privacy and security analysis of cryptography methods for the Web of Medical Things (WoMT)
- Presents case studies on the next generation medical chair, electronic nose and pill cam are also presented.
Zielgruppe
Academic and Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction to Medical Big Data Analytics. Introduction to IoT Devices and Health Bioinformatics. Part A: IoT in Life Sciences. 1. IoT and Robotics in Healthcare. 2. Implantable Electronics: Integration of Bio-interfaces, Devices and Sensors. 3. Electronic Devices, Circuits and Systems for Non-Invasive Diagnosis. 4. Internet of Things for Remote Healthcare and Health Monitoring. 5. Medical Electronics, Biomedical Instrumentations. 6. Surface Imaging for Bio-medical Applications. 7. Radiofrequency Devices, Circuits and Systems for e-Medicine. 8. Network Architectures and Frameworks for IoT Medical Applications. 9. Medical Big Data Management Systems and Infrastructures. Part B: Telemedicine and Health Care. 10. Disease Management, Auto-Administer Therapies. 11. Recommender Systems and Decision Support Systems. 12. Human Machine Interfaces. 13. Telemedicine and Mobile Applications- Healthcare. Part C: Medical Big Data Mining and Processing. 11. Big Data Mining Methods in Medical Applications. 12. Pattern Recognition, Features Extraction, Feature Reduction and Selection Techniques in Biomedical Applications.13. Classifiers in Biomedical and Healthcare Applications. Part D: Case studies for Classification in Medical Problems. 14. Applications. 15. Privacy and Security Issues in Big Data. 16. Standards, Challenges, and Recommendations for Advanced Classifiers in Medical Applications.