Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

Saved in:
Bibliographic Details
Title: Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.
Authors: Gehrmann S; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Harvard SEAS, Harvard University, Cambridge, MA, United States of America., Dernoncourt F; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Massachusetts Institute of Technology, Cambridge, MA, United States of America.; Adobe Research, San Jose, CA, United States of America., Li Y; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Harvard T.H. Chan School of Public Health, Cambridge, MA, United States of America., Carlson ET; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Philips Research North America, Cambridge, MA, United States of America., Wu JT; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Harvard T.H. Chan School of Public Health, Cambridge, MA, United States of America., Welt J; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA, United States of America., Foote J Jr; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Tufts University School of Medicine, Cambridge, MA, United States of America., Moseley ET; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; College of Science and Mathematics, University of Massachusetts, Boston, MA, United States of America., Grant DW; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Department of Surgery, Division of Plastic and Reconstructive Surgery, Washington University School of Medicine, St. Louis, MO, United States of America., Tyler PD; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Department of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States of America., Celi LA; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Massachusetts Institute of Technology, Cambridge, MA, United States of America.
Source: PloS one [PLoS One] 2018 Feb 15; Vol. 13 (2), pp. e0192360. Date of Electronic Publication: 2018 Feb 15 (Print Publication: 2018).
Publication Type: Comparative Study; Journal Article; Research Support, Non-U.S. Gov't
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: 29447188
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Gehrmann+S%22">Gehrmann S</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Harvard SEAS, Harvard University, Cambridge, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Dernoncourt+F%22">Dernoncourt F</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Massachusetts Institute of Technology, Cambridge, MA, United States of America.; Adobe Research, San Jose, CA, United States of America.<br /><searchLink fieldCode="AU" term="%22Li+Y%22">Li Y</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Harvard T.H. Chan School of Public Health, Cambridge, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Carlson+ET%22">Carlson ET</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Philips Research North America, Cambridge, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Wu+JT%22">Wu JT</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Harvard T.H. Chan School of Public Health, Cambridge, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Welt+J%22">Welt J</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Foote+J+Jr%22">Foote J Jr</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Tufts University School of Medicine, Cambridge, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Moseley+ET%22">Moseley ET</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; College of Science and Mathematics, University of Massachusetts, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Grant+DW%22">Grant DW</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Department of Surgery, Division of Plastic and Reconstructive Surgery, Washington University School of Medicine, St. Louis, MO, United States of America.<br /><searchLink fieldCode="AU" term="%22Tyler+PD%22">Tyler PD</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Department of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Celi+LA%22">Celi LA</searchLink>; MIT Critical Data, Laboratory for Computational Physiology, Cambridge, MA, United States of America.; Massachusetts Institute of Technology, Cambridge, MA, United States of America.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101285081%22">PloS one</searchLink> [PLoS One] 2018 Feb 15; Vol. 13 (2), pp. e0192360. <i>Date of Electronic Publication: </i>2018 Feb 15 (<i>Print Publication: </i>2018).
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Comparative Study; Journal Article; Research Support, Non-U.S. Gov't
– 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=29447188
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1371/journal.pone.0192360
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: e0192360
    Titles:
      – TitleFull: Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Gehrmann S
      – PersonEntity:
          Name:
            NameFull: Dernoncourt F
      – PersonEntity:
          Name:
            NameFull: Li Y
      – PersonEntity:
          Name:
            NameFull: Carlson ET
      – PersonEntity:
          Name:
            NameFull: Wu JT
      – PersonEntity:
          Name:
            NameFull: Welt J
      – PersonEntity:
          Name:
            NameFull: Foote J Jr
      – PersonEntity:
          Name:
            NameFull: Moseley ET
      – PersonEntity:
          Name:
            NameFull: Grant DW
      – PersonEntity:
          Name:
            NameFull: Tyler PD
      – PersonEntity:
          Name:
            NameFull: Celi LA
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 02
              Text: 2018 Feb 15
              Type: published
              Y: 2018
          Identifiers:
            – Type: issn-electronic
              Value: 1932-6203
          Numbering:
            – Type: volume
              Value: 13
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: PloS one
              Type: main
ResultId 1