Big Healthcare Data Analytics: Challenges and Applications

Increasing demand and costs for healthcare, exacerbated by ageing populations and a great shortage of doctors, are serious concerns worldwide. Consequently, this has generated a great amount of motivation in providing better healthcare through smarter healthcare systems. Management and processing of healthcare data are challenging due to various factors that are inherent in the data itself such as high-dimensionality, irregularity and sparsity. A long stream of research has been proposed to address these problems and provide more efficient and scalable healthcare systems and solutions. In this chapter, we shall examine the challenges in Chonho Lee’s work was done while he was at National University of Singapore. C. Lee Osaka University, Suita, Japan e-mail: [email protected] Z. Luo ⋅ K.Y. Ngiam ⋅ K. Zheng ⋅ B.C. Ooi ⋅ W.L.J. Yip National University of Singapore, Singapore, Singapore e-mail: [email protected] K.Y. Ngiam e-mail: [email protected] K. Zheng e-mail: [email protected] B.C. Ooi e-mail: [email protected] W.L.J. Yip e-mail: [email protected] K.Y. Ngiam ⋅W.L.J. Yip National University Hospital, Singapore, Singapore M. Zhang (✉) Singapore University of Technology and Design, Singapore, Singapore e-mail: [email protected] G. Chen Zhejiang University, Hangzhou, China e-mail: [email protected] © Springer International Publishing AG 2017 S.U. Khan et al. (eds.), Handbook of Large-Scale Distributed Computing in Smart Healthcare, Scalable Computing and Communications, DOI 10.1007/978-3-319-58280-1_2 11