Sensitivity Analysis of Stroke Predictors Using Structural Equation Modeling and Bayesian Networks-Reference-Cited by-同舟云学术

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Sensitivity Analysis of Stroke Predictors Using Structural Equation Modeling and Bayesian Networks

Published:2022-08-15 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
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Author:

Oliveira Helder C. R.¹,Yanushkevich Svetlana¹,Almekhlafi Mohammed²

Affiliation:

1. Schulich School of Engineering, University of Calgary,Biometric Technologies Laboratory,Department of Electrical and Software Engineering,Calgary,AB,Canada

2. Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary,Calgary,AB,Canada

Funder

Natural Sciences and Engineering Research Council of Canada (NSERC)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9862939/9863009/09863028.pdf?arnumber=9863028

Reference25 articles.

1. Epidemic Attack on the Aircraft Carrier Theodore Roosevelt: Bridging the Gaps in Emergency Management

2. Excess Body Weight and Incidence of Stroke

3. Association of Body Mass Index with Ischemic and Hemorrhagic Stroke

4. Influence of age on links between major modifiable risk factors and stroke occurrence in West Africa

5. Performance Analysis of Machine Learning Approaches in Stroke Prediction

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1. Combining real data and expert knowledge to build a Bayesian Network — Application to assess multiple risk factors for fall among elderly people;Expert Systems with Applications;2024-10

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