Seq2Seq Deep Learning Architecture Based COVID-19 Infected Patient Severity Prediction Using Electronic Health Records

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Publication Details

Journal
Korean Journal of Healthcare-Associated Infection Control and Prevention
Published
2024-12-27
DOI
https://doi.org/10.14192/kjicp.2024.29.2.146
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00

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article

Seq2Seq Deep Learning Architecture Based COVID-19 Infected Patient Severity Prediction Using Electronic Health Records

Inuk Jung, Ki Tae Kwon, Seung Hwan Bae
Korean Journal of Healthcare-Associated Infection Control and Prevention
Machine Learning in Healthcare
article

Seq2Seq Deep Learning Architecture Based COVID-19 Infected Patient Severity Prediction Using Electronic Health Records

Inuk Jung, Ki Tae Kwon, Seung Hwan Bae
article en

Abstract

No abstract available for this paper.
Korean Journal of Healthcare-Associated Infection Control and PreventionVol. 29(2)
Kyungpook National University (KR)
Korea Disease Control and Prevention Agency, Ministry of Health and Welfare
Openalex Percentile: Top 78%
Machine Learning in Healthcare
DOIOpen Access PDFOpenAlex
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Seq2Seq Deep Learning Architecture Based COVID-19 Infected Patient Severity Prediction Using Electronic Health Records — Inuk Jung, Ki Tae Kwon, et al. · Korean Journal of Healthcare-Associated Infection Control and Prevention (2024) | TGRS Research Map | TGRS