Special Issue - Enabling Technologies in Intelligent Healthcare (Call for Manuscripts)
The interaction between healthcare and technology has a rich history. However, the proliferation of the Artificial Intelligence (AI), Big Data, rapid world-wide development, and public embracement of miniature wearable biosensors, as well as the emerging field of Internet of Things (IoT) and Blockchain, have vastly expanded the possibilities to fulfill many existing healthcare needs. The rapid growth of deployed devices and technologies in medical fields has generated new opportunities for personalized eHealth and mHealth services. However, many challenges still need to be addressed in order to develop consistent, suitable, safe, flexible and power-efficient systems fit for medical needs. To enable this transformation, we need a large number of significant technological advancements in the hardware and software communities to come together. Novel advances in many related areas from bioelectronics, communication devices, software, and networks, to pattern recognition, sophisticated data-analytics, Big Data and cloud computing, information technologies and media development need to be developed in order to enable next-generation sensing, control, and computing achieving the IoT vision for smarter healthcare. The use of AI-driven IoT for eHealth and mHealth and research advances in Big Data techniques for effective manipulation of large, multiscale, multimodal, distributed and heterogeneous data sets, play a significant role in the well-being. Its advantages include the availability and accessibility (anytime, anywhere), ability to personalize and tailor content, and cost-effective delivery. This special issue focuses on novel cross-layer techniques for smart eHealth and mHealth systems, by identifying new perspectives and highlighting impending research issues and challenges. In particular, this special issue addresses all important aspects of emerging technologies for smart healthcare-wearable sensors, body area sensors, advanced pervasive healthcare systems, and Big Data analytics that are aimed at providing telehealth interventions to individuals for healthier lifestyles. Authors are invited to submit high-quality papers containing original work from either academia or industry reporting novel advances in (but not limited to) the following topics:
• Internet of things for medical and healthcare applications
• Mobile and e-Health sensing
• Wearable, outdoor and home-based sensors
• Harvesting management and optimization
• Wearable and implantable computing and biosensors
• Cloud-enabled body sensor networks
• Secure middleware for eHealth and IoT
• Reprogrammable and reconfigurable embedded systems for eHealth
• eHealth traffic characterization
• eHealth oriented software architectures (Agent, SOA, Middleware, etc.)
• Big-data analytics, machine learning algorithms, and scalable/parallel/distributed algorithms
• Modern Architectures - Services Computing and Databases
• Cloud-based secure data collection techniques
• Lightweight and Homomorphic security protocols for IIoT
• Privacy-aware big data (pre-)processing techniques
• Scalable and high-performance computing
• Theory and practice of engineering semantic e-health systems, especially methods, means and best cases
• Fog computing/Edge clouds for health care cloud resource allocation and monitoring
• Privacy-preserving and Security approaches for large scale analytics
• Federated analysis and multi-party computation techniques
• Blockchain: Opportunities for health care
• Fault tolerance, reliability, and scalability
• Autonomic analysis, monitoring and situation alertness
• Case studies of smart eHealth architectures (telemedicine applications, health management applications, etc.)
Important Dates
Submissions Deadline: September 15, 2023
First Reviews Due: November 15, 2023
Revision Due: December 15, 2023
Second Reviews Due: January 15, 2024
Submission Guidelines
Manuscripts (MS Word or PDF format), formatted in a single column, with double spacing, 12 pt. font and numbered pages. An abstract of 250 words or fewer should be included. Author names and identification information must be restricted to a separate Title page (Title, author names, affiliation, contact details and brief 3 to 4 sentence bios.), to facilitate blind peer review. Other than these, there are no style restrictions (e.g. APA, IEEE etc.) for the initial submission. Manuscripts must be submitted here. Please choose "Special Issue - Enabling Technologies in Intelligent Healthcare" in the section dropdown when submitting manuscripts for this special issue.
Editors
Farshad Firouzi, Duke University (Farshad.firouzi@duke.edu)
Mahmoud Daneshmand, Stevens Institute of Technology (mdaneshm@stevens.edu)
Amir H Gandomi, University of Technology Sydney (Amirhossein.Gandomi@uts.edu.au)