Applying Deep Learning to Individual and Community Health Monitoring Data: A Survey - Details

Author：

Yao, Zhen-Jie (Yao, Zhen-Jie.) | Bi, Jie (Bi, Jie.) | Chen, Yi-Xin (Chen, Yi-Xin.)

Indexed by：

EI Scopus CSCD

Abstract：

In　the　recent　years,　deep　learning　models　have　addressed　many　problems　in　various　fields.　Meanwhile,　technology　development　has　spawned　the　big　data　in　healthcare　rapidly.　Nowadays,　application　of　deep　learning　to　solve　the　problems　in　healthcare　is　a　hot　research　direction.　This　paper　introduces　the　application　of　deep　learning　in　healthcare　extensively.　We　focus　on　7　application　areas　of　deep　learning,　which　are　electronic　health　records　(EHR),　electrocardiography　(ECG),　electroencephalogram　(EEG),　community　healthcare,　data　from　wearable　devices,　drug　analysis　and　genomics　analysis.　The　scope　of　this　paper　does　not　cover　medical　image　processing　since　other　researchers　have　already　substantially　reviewed　it.　In　addition,　we　analyze　the　merits　and　drawbacks　of　the　existing　works,　analyze　the　existing　challenges,　and　discuss　future　trends.　©　2018,　Institute　of　Automation,　Chinese　Academy　of　Sciences　and　Springer-Verlag　GmbH　Germany,　part　of　Springer　Nature.

Keyword：

Surveying Surveys Records management Deep neural networks Neural networks Health care Deep learning Electrocardiography Medical imaging Electroencephalography

Author Community：

[ 1 ] [Yao, Zhen-Jie]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing; 100124, China
[ 2 ] [Bi, Jie]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing; 100124, China
[ 3 ] [Chen, Yi-Xin]Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis; MO; 63130, United States