View in EDS HTML Full Text PDF Full Text

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

Saved in:
Bibliographic Details
Title: Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.
Authors: Ye Q; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China., Fang G; Department of Nephrology, Nanjing Jinling Hospital, General Hospital of Eastern Theatre Command, Nanjing, Jiangsu, China., Li L; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China., Li Q; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China., Yang Y; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China., Liu L; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Source: PloS one [PLoS One] 2026 Jul 02; Vol. 21 (7), pp. e0351468. Date of Electronic Publication: 2026 Jul 02 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 42391297
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Ye+Q%22">Ye Q</searchLink>; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.<br /><searchLink fieldCode="AU" term="%22Fang+G%22">Fang G</searchLink>; Department of Nephrology, Nanjing Jinling Hospital, General Hospital of Eastern Theatre Command, Nanjing, Jiangsu, China.<br /><searchLink fieldCode="AU" term="%22Li+L%22">Li L</searchLink>; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.<br /><searchLink fieldCode="AU" term="%22Li+Q%22">Li Q</searchLink>; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.<br /><searchLink fieldCode="AU" term="%22Yang+Y%22">Yang Y</searchLink>; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.<br /><searchLink fieldCode="AU" term="%22Liu+L%22">Liu L</searchLink>; Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101285081%22">PloS one</searchLink> [PLoS One] 2026 Jul 02; Vol. 21 (7), pp. e0351468. <i>Date of Electronic Publication: </i>2026 Jul 02 (<i>Print Publication: </i>2026).
– 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="%22Public+Library+of+Science%22">Public Library of Science </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101285081 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>1932-6203 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2219326203%22">19326203 </searchLink><i>NLM ISO Abbreviation: </i>PLoS One <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42391297
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1371/journal.pone.0351468
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: e0351468
    Titles:
      – TitleFull: Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ye Q
      – PersonEntity:
          Name:
            NameFull: Fang G
      – PersonEntity:
          Name:
            NameFull: Li L
      – PersonEntity:
          Name:
            NameFull: Li Q
      – PersonEntity:
          Name:
            NameFull: Yang Y
      – PersonEntity:
          Name:
            NameFull: Liu L
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 02
              M: 07
              Text: 2026 Jul 02
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1932-6203
          Numbering:
            – Type: volume
              Value: 21
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: PloS one
              Type: main
ResultId 1