Smart healthcare is revolutionizing the world by providing faster diagnosis and therapeutics. This technology is made feasible with sophisticated infrastructures that are made available everywhere. For instance, the early detection of Parkinson’s disease in the elderly and autism in children will pave the way for a better world and a better future.

Several healthcare systems are targeted towards these applications, which requires reliability. On the other hand, the systems designed should be a universal solution, making it viable for the practice among a variety of end-users. Recent hot topics such as IoT, Big Data, Cloud Computing, and Artificial Intelligence help to enable healthcare to become intelligent and realizable. The IoT enables data collection, Big Data provides data analysis, Cloud Computing offers computing, and Artificial Intelligence empowers predictive analytics. In addition to these, novel image acquisition systems are widely adopted in recent times for medical diagnosis. These image acquisition systems suffer from reduced information that can help the medical practitioner to arrive at faster conclusions. The optimization of these systems warrants new research developments to improve the image content. Overall, it can be concluded that intelligent health care systems are expected to make a huge difference in the medical field in the near future. Keeping these virtues in mind, optimization algorithms also play a crucial role in data delivery to end-users.

This Special Issue has two main aims. Firstly, it aims to provide a forum for effective culmination and dissemination of developments in IoT, Big Data, Cloud Computing, and Artificial Intelligence targeted towards intelligent systems in healthcare. Secondly, this Special Issue will describe numerous efficient algorithms that can be used for optimizing performance and hence improving reliability in smart healthcare. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Energy-aware optimization algorithms for IoT systems in healthcare
• Machine learning and deep learning in telemedicine optimization
• Security enhancement and optimization in medical cyber-physical systems
• Optimization of medical image acquisition and analysis system
• Decision algorithms and data aggregation algorithms in healthcare
• Data analytics and process management in healthcare
• Statistical tools in biomedicine
• Sensor fusion algorithms and process optimization in healthcare
• Artificial Intelligence-enabled data processing techniques in healthcare
• Optimization of biotelemetry and metasystems