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Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.

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Title: Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.
Authors: Lin YT; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan., Deng YX; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan., Tsai CL; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan., Huang CH; Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan., Fu LC; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Source: JMIR medical informatics [JMIR Med Inform] 2024 Apr 01; Vol. 12, pp. e48862. Date of Electronic Publication: 2024 Apr 01.
Publication Type: Journal Article
Journal Info: Publisher: JMIR Publications Country of Publication: Canada NLM ID: 101645109 Publication Model: Electronic Cited Medium: Print ISSN: 2291-9694 (Print) Linking ISSN: 22919694 NLM ISO Abbreviation: JMIR Med Inform Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Lin+YT%22">Lin YT</searchLink>; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.<br /><searchLink fieldCode="AU" term="%22Deng+YX%22">Deng YX</searchLink>; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, 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, Taipei, 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, Taipei, Taiwan.<br /><searchLink fieldCode="AU" term="%22Fu+LC%22">Fu LC</searchLink>; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22JMIR+Publications%22">JMIR Publications </searchLink><i>Country of Publication: </i>Canada <i>NLM ID: </i>101645109 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Print <i>ISSN: </i>2291-9694 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2222919694%22">22919694 </searchLink><i>NLM ISO Abbreviation: </i>JMIR Med Inform <i>Subsets: </i>PubMed not MEDLINE
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      – TitleFull: Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.
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              Text: 2024 Apr 01
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