The fight against infectious diseases is one of the greatest challenges faced by mankind. Infectious diseases pose a serious threat to human life across the entire globe and can also have an unprecedented impact on our day-to-day lives and the global economy. Computational intelligence technology and ubiquitous computing models have also attracted a lot of attention in recent years. Researchers have invested a lot of time and energy to analyze the source of epidemics and predict the spread of epidemics using computational intelligence technology and ubiquitous computing models.

Recently, many computational intelligence technologies have appeared, such as multi-view learning, transfer learning and deep learning, and so on. Multi-view learning is the branch of machine learning concerned with the analysis of multi-modal data, i.e. patterns represented by different sets of features extracted from multiple data sources. Transfer learning makes use of data or knowledge gained in solving one problem to help solve a different, albeit related problem. Deep learning is a rapidly advancing field in medical image processing, natural language understanding, and bioinformatics in recent years. In addition, with the development of ubiquitous computing, ubiquitous medical devices make it possible to monitor patients in their work, domiciliary, and institutional settings as well as enabling peripatetic clinicians to access clinical information and services for treatment of the patient outside of clinical organizations. How to obtain advanced models with both intelligence and perception by integrating emerging computational intelligence technology into the ubiquitous computing model, and solving problems such as source tracking or propagation prediction of infectious diseases, is a big challenge in current related technologies.

This Special Issue will focus on the advanced computational intelligence technology and ubiquitous computing for severity assessment and classification of infectious disease, infectious disease intelligent diagnosis, new feature extraction and representation of infectious disease data, and large-scale infectious disease data analysis. We invite authors to contribute original research or review articles in this field.

Potential topics include but are not limited to the following:

• Computational intelligence and ubiquitous computing for severity assessment and classification of infectious disease
• Computational intelligence and ubiquitous computing for infectious disease intelligent diagnosis
• Computational intelligence and ubiquitous computing for multimedia-based infectious disease intelligent diagnosis
• New feature extraction and representation algorithms for the detection and diagnosis of infectious disease
• Knowledge discovery and pattern recognition from large-scale infectious disease data