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

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Title: Deep learning to predict emergency department revisit using static and dynamic features (Deep Revisit): development and validation study.
Authors: Hsu SY; Department of Computer Science and Information Engineering, National Taiwan University, CSIE Der Tian Hall No. 1, Sec. 4, Roosevelt Road, Taipei, 106319, Taiwan., Jhu JY; Department of Computer Science and Information Engineering, National Taiwan University, CSIE Der Tian Hall No. 1, Sec. 4, Roosevelt Road, Taipei, 106319, Taiwan., Gao JW; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Zhongshan S. Rd, Taipei, 100, Taiwan., Huang CH; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Zhongshan S. Rd, Taipei, 100, Taiwan., Tsai CL; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Zhongshan S. Rd, Taipei, 100, Taiwan. chulintsai@ntuh.gov.tw., Fu LC; Department of Computer Science and Information Engineering, National Taiwan University, CSIE Der Tian Hall No. 1, Sec. 4, Roosevelt Road, Taipei, 106319, Taiwan. lichen@ntu.edu.tw.
Source: BioData mining [BioData Min] 2025 Dec 20; Vol. 18 (1), pp. 88. Date of Electronic Publication: 2025 Dec 20.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101319161 Publication Model: Electronic Cited Medium: Print ISSN: 1756-0381 (Print) Linking ISSN: 17560381 NLM ISO Abbreviation: BioData Min Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Deep learning to predict emergency department revisit using static and dynamic features (Deep Revisit): development and validation study.
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  Data: <searchLink fieldCode="AU" term="%22Hsu+SY%22">Hsu SY</searchLink>; Department of Computer Science and Information Engineering, National Taiwan University, CSIE Der Tian Hall No. 1, Sec. 4, Roosevelt Road, Taipei, 106319, Taiwan.<br /><searchLink fieldCode="AU" term="%22Jhu+JY%22">Jhu JY</searchLink>; Department of Computer Science and Information Engineering, National Taiwan University, CSIE Der Tian Hall No. 1, Sec. 4, Roosevelt Road, Taipei, 106319, Taiwan.<br /><searchLink fieldCode="AU" term="%22Gao+JW%22">Gao JW</searchLink>; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Zhongshan S. Rd, Taipei, 100, Taiwan.<br /><searchLink fieldCode="AU" term="%22Huang+CH%22">Huang CH</searchLink>; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Zhongshan S. Rd, Taipei, 100, Taiwan.<br /><searchLink fieldCode="AU" term="%22Tsai+CL%22">Tsai CL</searchLink>; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Zhongshan S. Rd, Taipei, 100, Taiwan. chulintsai@ntuh.gov.tw.<br /><searchLink fieldCode="AU" term="%22Fu+LC%22">Fu LC</searchLink>; Department of Computer Science and Information Engineering, National Taiwan University, CSIE Der Tian Hall No. 1, Sec. 4, Roosevelt Road, Taipei, 106319, Taiwan. lichen@ntu.edu.tw.
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  Data: <searchLink fieldCode="JN" term="%22101319161%22">BioData mining</searchLink> [BioData Min] 2025 Dec 20; Vol. 18 (1), pp. 88. <i>Date of Electronic Publication: </i>2025 Dec 20.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22BioMed+Central%22">BioMed Central </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101319161 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Print <i>ISSN: </i>1756-0381 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2217560381%22">17560381 </searchLink><i>NLM ISO Abbreviation: </i>BioData Min <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1186/s13040-025-00509-x
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              Text: 2025 Dec 20
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