DyGraphTrans: A temporal graph representation learning framework for modeling disease progression from Electronic Health Records

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-02-02
DOI
https://doi.org/10.64898/2026.01.28.702347
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00

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article

DyGraphTrans: A temporal graph representation learning framework for modeling disease progression from Electronic Health Records

Most Tahmina Rahman, Mohammad Olaimat, Serdar Bozdag, Alzheimer's Disease Neuroimaging Initiative
bioRxiv (Cold Spring Harbor Laboratory)
Machine Learning in Healthcare
article

DyGraphTrans: A temporal graph representation learning framework for modeling disease progression from Electronic Health Records

Most Tahmina Rahman, Mohammad Olaimat, Serdar Bozdag, Alzheimer's Disease Neuroimaging Initiative
article en

Abstract

No abstract available for this paper.
bioRxiv (Cold Spring Harbor Laboratory)
University of North Texas (US), University of South Florida (US)
University of North Texas, National Institutes of Health, National Institute on Aging, National Institute of General Medical Sciences
Good health and well-being
Openalex Percentile: Top 71%
Machine Learning in Healthcare
DOIOpen Access PDFOpenAlex
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