Population-Scale Pervasive Health

被引:13
作者
Althoff, Tim [1 ]
机构
[1] Stanford Univ, Comp Sci, Stanford, CA 94305 USA
关键词
bioinformatics; data analysis; healthcare; Internet of Things; Internet/Web technologies; mobile; pervasive computing; pervasive health; privacy; social media;
D O I
10.1109/MPRV.2017.3971134
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Population-scale pervasive health research attempts to harness large-scale data that has already been collected through commercial devices and web applications to study human behaviors and the links between that data and health and well-being. Leveraging these existing datasets enables studies of behaviors and health at an unprecedented scale, resolution, and duration relatively inexpensively and quickly. Yet although there are great advantages in leveraging large-scale datasets for individual and population health, specialized computational methods are needed to overcome the limitations of this approach. Here, the author reviews lessons learned from his own work and from the works of other researchers, and he presents current challenges and opportunities. © 2002-2012 IEEE.
引用
收藏
页码:75 / 79
页数:5
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