Reinforcing Preventative Healthcare Solutions with AI, Blockchain and Next Generation Networks

Dear Colleagues,

The rise of healthcare technology has provided tremendous support for patient monitoring, both at hospitals and in-home, with the aid of wearable body sensors. Advancements in both communication and Artificial Intelligence have led to significant changes in health monitoring in order to support early-stage diagnosis. For instance, a number of AI-supported solutions have been developed to diagnose cancer and heart-related diseases. With the recent COVID-19 pandemic, it has become evident that traditional healthcare solutions are not feasible in supporting global health issues. Numerous technological solutions have provided aid in preventing, controlling, and combating infectious diseases. It has also been noticed that the use of personal movement tracking and behavior modeling can significantly support in the control aspect of infectious diseases. For such a mechanism to be adapted widely, it cannot rely on traditional communication, storage, and processing solutions. New and innovative solutions that can adapt data and processing distributivity, self-learnability, and autonomy must be considered in order to revolutionize healthcare systems and achieve high quality levels in healthcare for citizens globally. More importantly, the proposed solutions must adhere to patient data privacy and security. Such solutions cannot be achieved without reliance on advanced wireless communication, networking, machine learning, and transaction processing techniques.

The emergence of advanced networking and communication solutions such as 5G and intelligent network softwarization, distributed edge-supported learning such as federated learning, and decentralized transaction processing such as blockchain, will play a significant role in early stage infectious and non-infectious disease detection, to prevent or control the spread of these diseases either within the patient’s body (e.g., cancer-related diseases) or at a community level (e.g., flu-like diseases). These advanced novel health-care systems will support efficient and reliable storage, processing, and sharing of real-time data collected at the edge. As such, better monitoring and detection will lead to healthier aging for citizens, and can provide support for more advanced IoT-related solutions to support rehabilitation. With that being said, this Special Issue considers the adaptation of distributed learning techniques within next generation networks, supported by advanced secure transaction processing technologies such as blockchain to reinforce preventative healthcare solutions. It aims at fostering high-quality research with emerging ideas, approaches, theories, frameworks, and practices in preventive healthcare technology. Researchers, developers, and industry experts are welcome to contribute to the following topics, or to closely related ones:

• Theories, models, and AI tools to enhance preventative healthcare systems.
• Securing patient health data using federated learning solutions and blockchain technology.
• Edge communication and distributed learning to support healthcare systems.
• Utilizing AI and wireless communication in the healthcare sector.
• Utilizing next generation networks to support healthcare systems.
• Modeling disease-spread and human behavior using AI methods.
• AI-supported applications and tools for rehabilitation.
• Secure health monitoring at the edge of the network through wearable sensors.
• Predictive disease-spread data analytics.
• Utilizing AI to monitor and analyze real-time health system IoT data.
• Optimizing the use of edge computing resources to enhance the healthcare infrastructure.

Dr. Ismaeel Al Ridhawi
Dr. Safa Otoum
Dr. Ali Karime
Prof. Nadra Guizani
Guest Editors

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