About the Book
This Book aims at promoting and facilitating exchanges of research knowledge and findings across different disciplines on the design and investigation of federated learning-based intelligent data analytics of secured IoT-health infrastructures. The Intelligent Health systems will continuously generate massive data that requires big medical data techniques to process.
The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making and more professional services. The IoT helps to design and develop the intelligent healthcare solutions assisted by data analytics and machine learning.
This book aims will provides the federated learning, security and privacy, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart health informatics.
This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real world challenges for building smart healthcare sectors.
The content of books can be classified in 3 important sections. Potential topics include but are not limited to the following:
- Part I “Data-driven Smart Healthcare Infrastructure”
- Part II “Computing and Learning Algorithms for Remote Healthcare”
- Part III “Remote Biomedical Data-driven Solutions and Management”
Topics of Interest
- Smart remote health ecosystem– an Introduction
- Intelligent infrastructure of ubiquitous health computing
- Cyber-physical systems and Blockchain for remote healthcare
- Future concepts of IoMT and remote healthcare
- Federated learning for smartness in healthcare services
- Healthcare infrastructures in future smart cities
- HPC for remote and robotic surgery
- Distributed Artificial intelligence for biomedical data analytics
- Data analytics tools and technologies for smart healthcare
- Machine learning and AI for federated learning
- Optimization of remote healthcare services
- IoMT-Based collaborative learning and artificial intelligence of medical things (AIoMT)
- Cloud/Fog/Edge computing for secured smart cities
- Supervised and unsupervised learning-based onboard processing for IoMT and remote healthcare
- Wearable sensors and pervasive computing for remote healthcare
- Green computing and communications for IoMT and remote healthcare
- Collaborative federated learning for multi-modal diagnosis
- Cloud based distributed healthcare tools
- Federated learning and analytics for COVID-19 Diagnosis
- Ubiquitous computing for remote health data delivery
- Deterministic and stochastic approaches for biomedical modeling
- Edge assisted healthcare data analytics using federated Learning
- Secured urban healthcare management
- Internet of Things for medical data-driven solutions
- Internet of Ambulance things, Telemedicine, Tele-health
- M-Health, e-Health, p-Health for health data management
- Service management in mobile hospitals
- Pervasive patient health monitoring system
- Federated aided remote diagnosis
- Advanced communication, computing and management for Healthcare data
- Ubiquitous Computing for Remote Healthcare and IoMT Data Transmission
- Remote and distributed access to healthcare scientific data: a validation model
How to Submit?
Prospective contributors are invited to submit chapter proposal along with title, all author details, ORCID, and tentative TOC to email@example.com with the subject “Springer-IHIAM’21”. Abstract should highlight the novelty and contribution of the proposed article.
- Dr. Chinmay Chakraborty, Birla Institute of Technology, Mesra, Jharkhand, India
- Dr. Mohammad R. Khosravi, Persian Gulf University, Bushehr, Iran
- There is no fee to be paid.
- Lead author of each chapter will receive one complimentary copy of the book
|Abstract Submission||20th June 2021|
|Full Chapter Submission||20th July 2021|
|Status Notification||30th July 2021|