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Development of an intelligent decision support system for ischemic stroke risk assessment in a population-based electronic health record database
Abstract
Intelligent decision support systems (IDSS) have been applied to tasks of disease management. Deep neural networks (DNNs) are artificial intelligent techniques to achieve high modeling power. The application of DNNs to large-scale data for estimating stroke risk needs to be assessed and validated. This study aims to apply a DNN for deriving a stroke predictive model using a big electronic health record database.
Figures
The 3 year and 8 year stroke rate of patients in the 5 risk categories in the testing datasets.
The 3 year and 8 year stroke rate of patients in the 5 risk categories in the testing datasets.
Authors
Chen-Ying Hung Chi-Chun Lee
Publication Date
2019/03/13
Journal
PLOS ONE
PLOS ONE 14
DOI
10.1371/journal.pone.0213007
Publisher
Public Library of Science