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Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation.

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Bibliographic Details
Title: Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation.
Authors: Liu, Siru1,2, Wright, Aileen P1,3, McCoy, Allison B1, Huang, Sean S1,3, Steitz, Bryan1, Wright, Adam1,3
Source: Journal of the American Medical Informatics Association; Jun2025, Vol. 32 Issue 6, p1032-1039, 8p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 185284492
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+the+American+Medical+Informatics+Association%22">Journal of the American Medical Informatics Association</searchLink>; Jun2025, Vol. 32 Issue 6, p1032-1039, 8p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=185284492
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1093/jamia/ocaf059
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 1032
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      – TitleFull: Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation.
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            NameFull: Liu, Siru
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            NameFull: Wright, Aileen P
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            NameFull: McCoy, Allison B
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            NameFull: Huang, Sean S
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            NameFull: Steitz, Bryan
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          Dates:
            – D: 01
              M: 06
              Text: Jun2025
              Type: published
              Y: 2025
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              Value: 10675027
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              Value: 32
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