The Internet of Medical Things (IoMT) has evolved into one of the most promising eras of the Internet of Things (IoT), which attracts researchers’ attention due to its widespread applicability in Smart Healthcare systems (SHS). An IoMT-based smart healthcare system is a collection of several smart medical devices and apps connected within the network to provide health information. In IoMT-based smart healthcare systems, sensors and medical devices securely transmit medical data to the server nodes without human intervention. Further, medical devices remotely monitor patient health conditions to improve the quality and efficacy of patient medical treatment. Some of the major components of smart healthcare systems are IoMT, medical sensors, artificial intelligence (AI), 5G, big data, edge computing, and cloud computing. 

The AI-driven IoMT healthcare system is a combination of IoT (used for periodic control) and AI (used for data analysis). This combination makes the healthcare system more intelligent over time. AI-driven IoMT systems collect huge amounts of data generated by IoT and provide automated medical diagnostics to support inexpensive and superior personalized care based on complex analysis algorithms. AI can provide an enhanced user interface for real-time disease management and prevention. AI can further be utilized to provide security in the IoMT by detecting network intrusion within the system, detecting intermediary security attacks inside the IoMT, and conducting web-based security assessments using IoMT-enabled devices. 

The session on the Internet of Medical Things (IoMT) in Smart Healthcare Systems is pleased to announce a Special Issue aimed at showcasing the latest advancements and research in the field of IoMT and its applications in the realm of SHS. This special session will provide a platform for researchers, practitioners, and industry professionals to share their innovative ideas, insights, and solutions pertaining to the integration of IoMT technologies in healthcare. 

Topics of interest include, but are not limited to, the following: 

• Artificial intelligence-based IoMT for Smart Healthcare. 

• IoMT-based Health Monitoring and Prediction.

• Energy-efficient IoMT Architecture for Smart Healthcare 

• IoMT security and Privacy 

• Deep learning and transfer learning for smart healthcare 

• Computational intelligence in smart healthcare

• Edge-IoMT-Based Smart Healthcare System

• Data analytics in AI-IoMT 

• Clinical data collection, integration, and analysis in IoMT 

• Innovative IoMT solutions

• Wearable IoMT for smart healthcare

• Trustworthy AI and IoMT 

• Health disparity and IoMT Session Organizers