Disease Diagnosis in Smart Healthcare: Innovation, Technologies and Applications
Kwok Tai Chui,
Wadee Alhalabi,
Sally Shuk Han Pang,
Patricia Ordóñez de Pablos,
Ryan Wen Liu and
Mingbo Zhao
Additional contact information
Kwok Tai Chui: Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
Wadee Alhalabi: Virtual Reality Research Center, Effat University, Jeddah 21577, Saudi Arabia
Sally Shuk Han Pang: School of Biological Sciences, Faculty of Science, The University of Hong Kong, Hong Kong, China
Patricia Ordóñez de Pablos: Department of Business Administration and Accountability, Faculty of Economics, The University of Oviedo, 33003 Oviedo, Spain
Ryan Wen Liu: Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan 430063, China
Mingbo Zhao: School of Information Science & Technology, Donghua University, Shanghai 200051, China
Sustainability, 2017, vol. 9, issue 12, 1-23
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.
Keywords: automation; computational intelligence; data analysis; data mining; disease diagnosis; healthcare; smart living; smart city; social progress; sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:9:y:2017:i:12:p:2309-:d:123284
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