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. |
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| 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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