Identifying heart disease risk factors from electronic health records using an ensemble of deep learning method-Reference-Cited by-同舟云学术

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Identifying heart disease risk factors from electronic health records using an ensemble of deep learning method

Published:2023-05-02 Issue:3 Volume:13 Page:237-247
ISSN:2472-5579
Container-title:IISE Transactions on Healthcare Systems Engineering
language:en
Short-container-title:IISE Transactions on Healthcare Systems Engineering

Author:

Luo Linkai¹,Wang Yue¹^ORCID,Mo Daniel Y.¹^ORCID

Affiliation:

1. Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong, China

Publisher

Informa UK Limited

Subject

Public Health, Environmental and Occupational Health,Safety Research,Safety, Risk, Reliability and Quality

Link

https://www.tandfonline.com/doi/pdf/10.1080/24725579.2023.2205665

Reference41 articles.

1. Ba, J. L., Kiros, J. R. & Hinton, G. E. (2016). Layer normalization. arXiv preprint, arXiv:1607.06450.

2. CDC. (2022). Heart disease facts. Retrieved Feb 2023, from https://www.cdc.gov/heartdisease/facts.htm

3. A context-aware approach for progression tracking of medical concepts in electronic medical records

4. Hidden Markov model using Dirichlet process for de-identification

5. Identifying Risk Factors For Heart Disease in Electronic Medical Records: A Deep Learning Approach

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