Deep learning to predict emergency department revisit using static and dynamic features (Deep Revisit): development and validation study

Our model significantly outperformed the static-only baseline. It demonstrates the effectiveness of multimodal clinical data fusion in improving ED revisit prediction and supporting clinical decision-making.

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Publication Details

Journal
BioData Mining
Published
2025-12-20
DOI
https://doi.org/10.1186/s13040-025-00509-x
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Deep learning to predict emergency department revisit using static and dynamic features (Deep Revisit): development and validation study

Su-Yin Hsu, Jin-Yuan Jhu, Chu‐Lin Tsai, Li‐Chen Fu et al.
BioData Mining
Emergency and Acute Care Studies
article

Deep learning to predict emergency department revisit using static and dynamic features (Deep Revisit): development and validation study

Su-Yin Hsu, Jin-Yuan Jhu, Chu‐Lin Tsai, Li‐Chen Fu, Jinyao Gao, Chien-Hua Huang
article en

Abstract

Our model significantly outperformed the static-only baseline. It demonstrates the effectiveness of multimodal clinical data fusion in improving ED revisit prediction and supporting clinical decision-making.

BioData MiningVol. 18(1)
National Taiwan University (TW), National Taiwan University Hospital (TW)
Openalex Percentile: Top 43%
Emergency and Acute Care Studies
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