Edge-of-Things in Personalized Healthcare Support Systems discusses and explores state-of-the-art technology developments in storage and sharing of personal healthcare records in a secure manner that is globally distributed to incorporate best healthcare practices. The book presents research into the identification of specialization and expertise among healthcare professionals, the sharing of records over the cloud, access controls and rights of shared documents, document privacy, as well as edge computing techniques which help to identify causes and develop treatments for human disease. The…mehr
Edge-of-Things in Personalized Healthcare Support Systems discusses and explores state-of-the-art technology developments in storage and sharing of personal healthcare records in a secure manner that is globally distributed to incorporate best healthcare practices. The book presents research into the identification of specialization and expertise among healthcare professionals, the sharing of records over the cloud, access controls and rights of shared documents, document privacy, as well as edge computing techniques which help to identify causes and develop treatments for human disease. The book aims to advance personal healthcare, medical diagnosis, and treatment by applying IoT, cloud, and edge computing technologies in association with effective data analytics. Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Rajeswari Sridhar is currently working as an Associate Professor in the Department of Computer Science and Engineering at the National Institute of Technology, Tiruchirappalli, India. Her research interests include Cloud computing, Natural language processing, Information Retrieval, etc. She has guided 2 PhD students in the areas of Resource provisioning in Cloud computing and Access policies for data sharing through the cloud. She is currently guiding 5 research scholars in similar areas. She has published 70 articles in reputed journals and conferences. She is a member of the IEEE, ACM and CSI.
G R Gangadharan is working as an Associate Professor in the National Institute of Technology, Tiruchirappalli, India. His research interests are mainly located on the interface between technological and business perspectives. He has published around 95 publications in the reputed international journals, conferences, and book chapters. He has also edited two books. He has received Ph.D. degree in Information and Communication Technology (2008) from the University of Trento, Trento, Italy and European University Association and an M.S. in Information Technology (2004) from Scuola Superiore Sant'Anna, Pisa, Italy. He is a Senior Member of IEEE and ACM.
Inhaltsangabe
1. Exploring the dichotomy on opportunities and challenges of smart technologies in healthcare systems 2. The architecture of smartness in healthcare 3. Personalized decision support for cardiology based on deep learning: an overview 4. Data-driven models for cuffless blood pressure estimation using ECG and PPG signals 5. A recommendation system for the prediction of drug-target associations 6. Towards building an efficient deep neural network based on YOLO detector for fetal head localization from ultrasound images 7. FunNet: a deep learning network for the detection of age-related macular degeneration 8. An improved method for automated detection of microaneurysm in retinal fundus images 9. Integration and study of map matching algorithms in healthcare services for cognitive impaired person 10. Emotion-recognition-based music therapy system using electroencephalography signals 11. Feedback context-aware pervasive systems in healthcare management: a Boolean Network approach 12. Mental stress detection using a wearable device and heart rate variability monitoring 13. Knowledge discovery and presentation using social media analysis in health domain 14. Computationally efficient integrity verification for shared data in cloud storage 15. Intelligent analysis of multimedia healthcare data using natural language processing and deep-learning techniques 16. Measurement of the effects of parks on air pollution in megacities: do parks support health betterment? 17. Internet of Things use case applications for COVID-19
1. Exploring the dichotomy on opportunities and challenges of smart technologies in healthcare systems 2. The architecture of smartness in healthcare 3. Personalized decision support for cardiology based on deep learning: an overview 4. Data-driven models for cuffless blood pressure estimation using ECG and PPG signals 5. A recommendation system for the prediction of drug-target associations 6. Towards building an efficient deep neural network based on YOLO detector for fetal head localization from ultrasound images 7. FunNet: a deep learning network for the detection of age-related macular degeneration 8. An improved method for automated detection of microaneurysm in retinal fundus images 9. Integration and study of map matching algorithms in healthcare services for cognitive impaired person 10. Emotion-recognition-based music therapy system using electroencephalography signals 11. Feedback context-aware pervasive systems in healthcare management: a Boolean Network approach 12. Mental stress detection using a wearable device and heart rate variability monitoring 13. Knowledge discovery and presentation using social media analysis in health domain 14. Computationally efficient integrity verification for shared data in cloud storage 15. Intelligent analysis of multimedia healthcare data using natural language processing and deep-learning techniques 16. Measurement of the effects of parks on air pollution in megacities: do parks support health betterment? 17. Internet of Things use case applications for COVID-19
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