With recent advancements in medical biology and health informatics, the disease and treatment research data generated by multi-omics techniques (such as proteomics, metabonomics, genomics, and transcriptionomics) and various molecular biology and health informatics techniques have grown exponentially, and the nature of such data is increasingly complex. This poses a great challenge on how to design a new healthcare information system for efficient data processing, analysis, and modelling in medical research, pharmaceutical screening, and clinical applications, as well as how to understand the underlying molecular biological process.

There are many advantages to be gained with the application in healthcare of advances in machine learning and big data, however, there are many challenges in providing systems accurate enough to be useful to clinicians and patients. Not only are large amounts of data available, but sensitivity and specificity must be paid special attention, as well as ensuring support systems fit rationally into the health system. Recently, fog/edge computing has become a promising paradigm for healthcare information systems. The basic idea is to leverage a multitude of cooperative fog/edge devices and near-user infrastructures to carry out a substantial amount of computation, storage, and communication for the construction of cyber-physical frameworks, hybrid intelligent systems, distributed analytics, and detection systems. Despite the many benefits and opportunities fog/edge assistance offers, there are several challenges that need attention from the research community. Some of these challenges include designing an intelligent fog/edge assisted urban information collection and management framework, making textual and visual information retrieval more intelligent, achieving new principled information retrieval models or algorithms with sound empirical validation and fog/edge assistance, designing complex content (text, image, speech, or video) analysis methods to support the user interface recommender (UIR), and designing fog/edge assisted computational models of user information preferences and interaction behaviors in healthcare informatics.

The aim of this Special Issue is to gather new advances in the use of intelligent fog-edge computing in healthcare informatics. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Fog/edge computing in mobile healthcare systems
• Mobile healthcare systems using fog/edge computing
• Healthcare informatics in social media using fog/edge computing
• Internet of Things healthcare informatics using fog/edge computing
• Wearable medical equipment system using fog/edge computing
• Early identification of disease using fog/edge computing
• Fog/edge assisted emerging urban services and applications