Medical Internet of Things
Perspectives, Impact and Challenges
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49 447 Ft
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A termék adatai:
- Kiadás sorszáma 1
- Kiadó CRC Press
- Megjelenés dátuma 2026. április 21.
- ISBN 9781041085355
- Kötéstípus Keménykötés
- Terjedelem432 oldal
- Méret 234x156 mm
- Nyelv angol
- Illusztrációk 122 Illustrations, black & white; 9 Illustrations, color; 27 Halftones, black & white; 1 Halftones, color; 95 Line drawings, black & white; 8 Line drawings, color; 57 Tables, black & white 700
Kategóriák
Rövid leírás:
MIoT's potential to revolutionize healthcare is vast, offering unprecedented opportunities for improved patient care and operational efficiency. As MIoT continues to evolve, balancing innovation with privacy and security will be crucial to fostering trust, ensuring compliance, and maximizing the benefits of this technology in healthcare.
TöbbHosszú leírás:
The Medical Internet of Things (MIoT) has redefined healthcare by interconnecting devices, systems, and applications to monitor, analyze, and manage patient data in real time. MIoT leverages wearable devices, sensors, and interconnected medical equipment, enabling remote health monitoring, precision medicine, and improved patient outcomes. By seamlessly integrating patient data from various sources, MIoT leads to early diagnosis, treatment optimization, and personalized healthcare interventions. With this interconnectedness, healthcare professionals gain continuous access to patient vitals, enhancing diagnostic accuracy and response times, particularly in remote and underserved areas. This real-time data flow also facilitates predictive analytics, helping pre-empt adverse events and reducing hospital readmissions. However, MIoT also raises significant challenges, including concerns about data privacy, security, and the risk of cyber threats. The vast amounts of sensitive patient information shared across networks make privacy safeguards and robust security mechanisms essential to protect patient confidentiality and data integrity.
The potential of MIoT to revolutionize healthcare is vast, offering unprecedented opportunities for improved patient care and operational efficiency. As MIoT continues to evolve, balancing innovation with privacy and security will be crucial to fostering trust, ensuring compliance, and maximizing the benefits of this technology in healthcare.
TöbbTartalomjegyzék:
Preface. 1. Smart Hospital and Healthcare Facilities. 2. Benefits of Surgical Robots. 3. Monitoring Medication Adherence: Methods, Tools, and Outcomes. 4. Integrating Smart Solutions for Healthcare and Environmental Surveillance. 5. Data Privacy in Healthcare: A Focus on MIoT Devices. 6. Big Data-based Advancements in Prostate Cancer Imaging: Artificial Intelligence-based Segmentation of Ga-PSMA PET for Tumor Volume Assessment. 7. Healthcare Data and Analytics in Medical Internet of Things (MIoT). 8. Wearable and Implantable Medical Internet of Things Devices. 9. Ultrasound Medical Image Denoising Using Block-matching and 3D-filtering with the Alternating Direction Method of Multipliers. 10. Role of 5G and Future Connectivity in MIoT. 11. Pharmacovigilance-driven Personalized Treatment Using Genomic and Medical IoT Data. 12. An Adaptive and Intelligent IoT Framework for Next Generation Rehabilitation. 13. Augmented and Virtual Reality in MIoT: Transforming Patient Care, Training, and Telemedicine. 14. Blockchain for Smart Healthcare: A Survey. 15. Integrating Blockchain and Digital Twin for Secure Drug Tracking and Personalized Medication in Smart Pharma. 16. Healthcare and Pharmaceuticals Applications. 17. Data Privacy and Confidentiality in Medical Internet of Things (MIoT). 18. Empowering Health through Intelligent Insights: Dr. Symptoms – Your Pathway to Wellness. 19. Intelligent Detection of Physical Activity and Functional Fitness Level Using Smartphone Sensors by Deep Learning Techniques. 20. Pharmaceutical Integrity and MIoT System: Ethical, Legal, and Halal Bioethical Perspectives. 21. Healthcare IoT: Trends, Application Demands, and Security Issues in Clinical IoT. 22. Label Efficient Active Learning for Coronary Artery Disease Detection and False Negatives Elimination. Index.
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