View in EDS

Optimizing large language models for detecting symptoms of depression/anxiety in chronic diseases patient communications.

Saved in:
Bibliographic Details
Title: Optimizing large language models for detecting symptoms of depression/anxiety in chronic diseases patient communications.
Authors: Kim J; Stanford Center for Digital Health, Department of Medicine, Stanford University, Stanford, CA, USA. jykim3@stanford.edu., Ma SP; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Technology and Digital Solutions, School of Medicine, Stanford University, Stanford, CA, USA.; Stanford Health Care, Palo Alto, CA, USA., Chen ML; Stanford Center for Digital Health, Department of Medicine, Stanford University, Stanford, CA, USA., Galatzer-Levy IR; Google LLC, Mountain View, CA, USA., Torous J; Division of Digital Psychiatry, Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA., van Roessel PJ; Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Palo Alto, CA, USA., Sharp C; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Technology and Digital Solutions, School of Medicine, Stanford University, Stanford, CA, USA.; Stanford Health Care, Palo Alto, CA, USA., Pfeffer MA; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Technology and Digital Solutions, School of Medicine, Stanford University, Stanford, CA, USA.; Stanford Health Care, Palo Alto, CA, USA., Rodriguez CI; Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Palo Alto, CA, USA.; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA., Linos E; Stanford Center for Digital Health, Department of Medicine, Stanford University, Stanford, CA, USA., Chen JH; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA.
Source: NPJ digital medicine [NPJ Digit Med] 2025 Sep 30; Vol. 8 (1), pp. 580. Date of Electronic Publication: 2025 Sep 30.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41028413
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Optimizing large language models for detecting symptoms of depression/anxiety in chronic diseases patient communications.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Kim+J%22">Kim J</searchLink>; Stanford Center for Digital Health, Department of Medicine, Stanford University, Stanford, CA, USA. jykim3@stanford.edu.<br /><searchLink fieldCode="AU" term="%22Ma+SP%22">Ma SP</searchLink>; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Technology and Digital Solutions, School of Medicine, Stanford University, Stanford, CA, USA.; Stanford Health Care, Palo Alto, CA, USA.<br /><searchLink fieldCode="AU" term="%22Chen+ML%22">Chen ML</searchLink>; Stanford Center for Digital Health, Department of Medicine, Stanford University, Stanford, CA, USA.<br /><searchLink fieldCode="AU" term="%22Galatzer-Levy+IR%22">Galatzer-Levy IR</searchLink>; Google LLC, Mountain View, CA, USA.<br /><searchLink fieldCode="AU" term="%22Torous+J%22">Torous J</searchLink>; Division of Digital Psychiatry, Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22van+Roessel+PJ%22">van Roessel PJ</searchLink>; Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Palo Alto, CA, USA.<br /><searchLink fieldCode="AU" term="%22Sharp+C%22">Sharp C</searchLink>; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Technology and Digital Solutions, School of Medicine, Stanford University, Stanford, CA, USA.; Stanford Health Care, Palo Alto, CA, USA.<br /><searchLink fieldCode="AU" term="%22Pfeffer+MA%22">Pfeffer MA</searchLink>; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Technology and Digital Solutions, School of Medicine, Stanford University, Stanford, CA, USA.; Stanford Health Care, Palo Alto, CA, USA.<br /><searchLink fieldCode="AU" term="%22Rodriguez+CI%22">Rodriguez CI</searchLink>; Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Palo Alto, CA, USA.; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA.<br /><searchLink fieldCode="AU" term="%22Linos+E%22">Linos E</searchLink>; Stanford Center for Digital Health, Department of Medicine, Stanford University, Stanford, CA, USA.<br /><searchLink fieldCode="AU" term="%22Chen+JH%22">Chen JH</searchLink>; Division of Hospital Medicine, Stanford School of Medicine, Stanford, CA, USA.; Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101731738%22">NPJ digital medicine</searchLink> [NPJ Digit Med] 2025 Sep 30; Vol. 8 (1), pp. 580. <i>Date of Electronic Publication: </i>2025 Sep 30.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Publishing+Group%22">Nature Publishing Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101731738 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2398-6352 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2223986352%22">23986352 </searchLink><i>NLM ISO Abbreviation: </i>NPJ Digit Med <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41028413
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1038/s41746-025-01969-5
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 580
    Titles:
      – TitleFull: Optimizing large language models for detecting symptoms of depression/anxiety in chronic diseases patient communications.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Kim J
      – PersonEntity:
          Name:
            NameFull: Ma SP
      – PersonEntity:
          Name:
            NameFull: Chen ML
      – PersonEntity:
          Name:
            NameFull: Galatzer-Levy IR
      – PersonEntity:
          Name:
            NameFull: Torous J
      – PersonEntity:
          Name:
            NameFull: van Roessel PJ
      – PersonEntity:
          Name:
            NameFull: Sharp C
      – PersonEntity:
          Name:
            NameFull: Pfeffer MA
      – PersonEntity:
          Name:
            NameFull: Rodriguez CI
      – PersonEntity:
          Name:
            NameFull: Linos E
      – PersonEntity:
          Name:
            NameFull: Chen JH
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 30
              M: 09
              Text: 2025 Sep 30
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-electronic
              Value: 2398-6352
          Numbering:
            – Type: volume
              Value: 8
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: NPJ digital medicine
              Type: main
ResultId 1