Metaheuristic Algorithms for Healthcare: Open Issues and Challenges. (July 2016)

• Record Type: Journal Article
• Authors: Tsai, Chun-Wei; Chiang, Ming-Chao; Ksentini, Adlen; Chen, Min
• Is Part Of: Computers & electrical engineering. Volume 53(2016)
• Page Start: 421
• Page End: 434
• Publication Date: 2016-07
• Subjects: Metaheuristic algorithm -- data -- healthcare -- and smart home; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.03.005
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A brief survey of metaheuristics for healthcare system is given. A learnable big data analytics framework for healthcare system is presented. Open issues and future trends of metaheuristics for healthcare system are addressed. Graphical abstract: Abstract: Inspired by the observation that a healthcare system usually involves various intelligent technologies from different disciplines, especially metaheuristics and data mining, this paper provides a brief survey of metaheuristics for healthcare system and a roadmap for researchers working on metaheuristics and healthcare to develop a more efficient and effective healthcare system. This paper begins with a discussion of changes for healthcare, followed by a brief review of the features of "up-to-date technologies for healthcare.". Then, a learnable big data analytics framework for healthcare system is presented which provides a high performance solution to the forthcoming challenges of big data. Finally, changes, potentials, open issues, and future trends of metaheuristics for healthcare are addressed.