Enabling efficient stroke prediction by exploring sleep related features

Jia Xie, Zhu Wang, Zhiwen Yu, Bin Guo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Stroke is one typical chronic disease, which is caused by the degenerative disorder of the central nervous system and has a serious impact on the daily lives of human beings. Thereby, it is of great value to enable early diagnosis or prediction of stroke by monitoring peoples daily physiological data and designing useful stroke predictors when the symptoms are not apparent. Specifically, in this paper, we propose a novel approach for stroke prediction by exploring sleep related features. In the first step, we present a stroke prediction framework, which integrates common medical features with fine-grained sleep features for stroke risk prediction. In the second step, we propose a stroke risk prediction model, which consists of two key components to control the false negative rate of stroke prediction. We evaluate the framework using a real polysomnogram dataset that contains 66 patients and 159 healthy individuals. Experimental results demonstrate that the proposed model can predict stroke events effectively, and the Precision, Recall and AUC are 83.1%, 83.6%, and 0.782, respectively.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018
EditorsFrederic Loulergue, Guojun Wang, Md Zakirul Alam Bhuiyan, Xiaoxing Ma, Peng Li, Manuel Roveri, Qi Han, Lei Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages452-461
Number of pages10
ISBN (Electronic)9781538693803
DOIs
StatePublished - 4 Dec 2018
Event4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 - Guangzhou, China
Duration: 7 Oct 201811 Oct 2018

Publication series

NameProceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018

Conference

Conference4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018
Country/TerritoryChina
CityGuangzhou
Period7/10/1811/10/18

Keywords

  • Sleep Cycle
  • Sleep Stage
  • Stroke

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