http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Combining visual intelligence and federated learning in smart healthcare
"The objective of this book aims to implement emerging technology to transforms images from the original grayscale and reveals hidden patterns, into new well-defined structured patterns empowering research community, and computer analytics to remove indicative uncertainty"-- Provided by publisher.
Preface -- Chapter 1.. 5W+1H Automated Testing in Healthcare: A Case Study -- Chapter 2.. AI, IoT, and Cognitive Computing for Mental Health Enhancement and Object Detection -- Chapter 3.. An Innovative Obstacle Detection Smart System for Robot Navigation in Healthcare Industry -- Chapter 4.. Enhancing Telemedicine Deep Learning-Based Classification of ECG Heartbeats: With Continuous Wavelet Transform for Remote Cardiac Care -- Chapter 5.. Integrating Machine Learning for Accurate Diagnostics and Real-Time Monitoring for Revolutionizing Healthcare With Visual Intelligence -- Chapter 6.. Integrating Visual Intelligence With Federated Learning and IoT in Healthcare -- Chapter 7.. IoT- Enhanced Additive Manufacturing and Federated Learning for Smart Healthcare Systems -- Chapter 8.. Study on Challenges and Future Prospects of Glomerulus-on- a- Chip: A Pathway for Future Kidney on Chip Technology -- Chapter 9.. Synergistic Integration of Federated Learning and Visual Intelligence for Disease Diagnosis and Prediction: Next-Gen Healthcare Landscape -- Chapter 10.. Unleashing Sensors and Wearable Technologies in Gauging Healthcare Transmuting Digital Health Technologies: Nurturing Innovation and Implementations in Human Augmentation -- Chapter 11.. Wearable Sensors, Real-Time Monitoring and Data Assimilation in Healthcare Resonates -- About the Contributors -- Index
[edited by] Manisha Guduri, Chinmay Chakraborty, Martin Margala.
Includes bibliographical references and index.
Hershey, PA : IGI Global Scientific Publishing, [2025]