Abstract:To promote sustainable development, the smart city implies a global vision that merges artificial intelligence, big data, decision making, information and communication technology (ICT), and the internet-of-things (IoT). The ageing issue is an aspect that researchers, companies and government should devote efforts in developing smart healthcare innovative technology and applications. In this paper, the topic of disease diagnosis in smart healthcare is reviewed. Typical emerging optimization algorithms and machine learning algorithms are summarized. Evolutionary optimization, stochastic optimization and combinatorial optimization are covered. Owning to the fact that there are plenty of applications in healthcare, four applications in the field of diseases diagnosis (which also list in the top 10 causes of global death in 2015), namely cardiovascular diseases, diabetes mellitus, Alzheimer's disease and other forms of dementia, and tuberculosis, are considered. In addition, challenges in the deployment of disease diagnosis in healthcare have been discussed.

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Fibers are proven to provide health benefits in preventing metabolic diseases. This chapter first presents the existing blood glucose monitoring sensors and a prediction model for blood glucose concentration. It also aims at analyzing the efficacy of a functional fiber, psyllium on the glycemic control function. Three studies included suggesting psyllium supplementation would significantly improve glycemic response while two studies included showed no effects. Advantages and limitations of each study were evaluated. Overall, it is generally believed that psyllium might give glycemic response improvement effect, especially in Type II Diabetes Mellitus patients.