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The Grey Markov Model Modification of Panel Data Prediction for Stroke Recurrence with Health Care Data

  • Beihang University

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

Abstract

It is a crucial method to propose a predictive model for recurrence of stroke by analyzing the diagnostic data of stroke inpatient from health care system in order to predict the disease relapse of patients with stroke. Stroke has high relapse rates and is an epidemic disease with high morbidity, high mortality, and high disability. The mortality rate of recurrent patients is much higher than its first onset, which means the implementation of targeted prevention measures based on the prediction result could effectively reduce the mortality.

Original languageEnglish
Title of host publication2018 Annual Reliability and Maintainability Symposium, RAMS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538628706
DOIs
StatePublished - 11 Sep 2018
Event2018 Annual Reliability and Maintainability Symposium, RAMS 2018 - Reno, United States
Duration: 22 Jan 201825 Jan 2018

Publication series

NameProceedings - Annual Reliability and Maintainability Symposium
Volume2018-January
ISSN (Print)0149-144X

Conference

Conference2018 Annual Reliability and Maintainability Symposium, RAMS 2018
Country/TerritoryUnited States
CityReno
Period22/01/1825/01/18

Keywords

  • Panel data
  • Predictive model
  • Stroke recurrence

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