View in EDS

Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data.

Saved in:
Bibliographic Details
Title: Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data.
Authors: Nakashima T; Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, USA.; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan., Ogata S; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan., Noguchi T; Department of Cardiovascular Medicine, National Cerebral and Cardiovascular Centre, Suita, Japan tnoguchi@ncvc.go.jp., Tahara Y; Department of Cardiovascular Medicine, National Cerebral and Cardiovascular Centre, Suita, Japan., Onozuka D; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan., Kato S; H.U. Group Research Institute G.K, Tokyo, Japan., Yamagata Y; National Institute for Environmental Studies, Tsukuba, Japan., Kojima S; Department of General Internal Medicine 3, Kawasaki Medical School, Kurashiki, Japan., Iwami T; Health Service, Kyoto University, Kyoto, Japan., Sakamoto T; Department of Emergency Medicine, Teikyo University, Itabashi-ku, Japan., Nagao K; Cardiovascular Centre, Nihon University Hospital, Tokyo, Japan., Nonogi H; Shizuoka General Hospital, Shizuoka, Japan., Yasuda S; Department of Cardiovascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan., Iihara K; National Cerebral and Cardiovascular Center, Suita, Osaka, Japan., Neumar R; Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, USA., Nishimura K; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan.
Source: Heart (British Cardiac Society) [Heart] 2021 Jun 11; Vol. 107 (13), pp. 1084-1091. Date of Electronic Publication: 2021 Jun 11.
Publication Type: Journal Article
Journal Info: Publisher: BMJ Pub. Group Country of Publication: England NLM ID: 9602087 Publication Model: Electronic Cited Medium: Internet ISSN: 1468-201X (Electronic) Linking ISSN: 13556037 NLM ISO Abbreviation: Heart Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 34001636
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Nakashima+T%22">Nakashima T</searchLink>; Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, USA.; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan.<br /><searchLink fieldCode="AU" term="%22Ogata+S%22">Ogata S</searchLink>; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan.<br /><searchLink fieldCode="AU" term="%22Noguchi+T%22">Noguchi T</searchLink>; Department of Cardiovascular Medicine, National Cerebral and Cardiovascular Centre, Suita, Japan tnoguchi@ncvc.go.jp.<br /><searchLink fieldCode="AU" term="%22Tahara+Y%22">Tahara Y</searchLink>; Department of Cardiovascular Medicine, National Cerebral and Cardiovascular Centre, Suita, Japan.<br /><searchLink fieldCode="AU" term="%22Onozuka+D%22">Onozuka D</searchLink>; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan.<br /><searchLink fieldCode="AU" term="%22Kato+S%22">Kato S</searchLink>; H.U. Group Research Institute G.K, Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Yamagata+Y%22">Yamagata Y</searchLink>; National Institute for Environmental Studies, Tsukuba, Japan.<br /><searchLink fieldCode="AU" term="%22Kojima+S%22">Kojima S</searchLink>; Department of General Internal Medicine 3, Kawasaki Medical School, Kurashiki, Japan.<br /><searchLink fieldCode="AU" term="%22Iwami+T%22">Iwami T</searchLink>; Health Service, Kyoto University, Kyoto, Japan.<br /><searchLink fieldCode="AU" term="%22Sakamoto+T%22">Sakamoto T</searchLink>; Department of Emergency Medicine, Teikyo University, Itabashi-ku, Japan.<br /><searchLink fieldCode="AU" term="%22Nagao+K%22">Nagao K</searchLink>; Cardiovascular Centre, Nihon University Hospital, Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Nonogi+H%22">Nonogi H</searchLink>; Shizuoka General Hospital, Shizuoka, Japan.<br /><searchLink fieldCode="AU" term="%22Yasuda+S%22">Yasuda S</searchLink>; Department of Cardiovascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan.<br /><searchLink fieldCode="AU" term="%22Iihara+K%22">Iihara K</searchLink>; National Cerebral and Cardiovascular Center, Suita, Osaka, Japan.<br /><searchLink fieldCode="AU" term="%22Neumar+R%22">Neumar R</searchLink>; Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, USA.<br /><searchLink fieldCode="AU" term="%22Nishimura+K%22">Nishimura K</searchLink>; Department of Preventive Medicine and Epidemiologic Informatics, National Cerebral Cardiovascular Centre, Suita, Japan.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%229602087%22">Heart (British Cardiac Society)</searchLink> [Heart] 2021 Jun 11; Vol. 107 (13), pp. 1084-1091. <i>Date of Electronic Publication: </i>2021 Jun 11.
– 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="%22BMJ+Pub%2E+Group%22">BMJ Pub. Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>9602087 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1468-201X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2213556037%22">13556037 </searchLink><i>NLM ISO Abbreviation: </i>Heart <i>Subsets: </i>MEDLINE; PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=34001636
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1136/heartjnl-2020-318726
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 1084
    Titles:
      – TitleFull: Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Nakashima T
      – PersonEntity:
          Name:
            NameFull: Ogata S
      – PersonEntity:
          Name:
            NameFull: Noguchi T
      – PersonEntity:
          Name:
            NameFull: Tahara Y
      – PersonEntity:
          Name:
            NameFull: Onozuka D
      – PersonEntity:
          Name:
            NameFull: Kato S
      – PersonEntity:
          Name:
            NameFull: Yamagata Y
      – PersonEntity:
          Name:
            NameFull: Kojima S
      – PersonEntity:
          Name:
            NameFull: Iwami T
      – PersonEntity:
          Name:
            NameFull: Sakamoto T
      – PersonEntity:
          Name:
            NameFull: Nagao K
      – PersonEntity:
          Name:
            NameFull: Nonogi H
      – PersonEntity:
          Name:
            NameFull: Yasuda S
      – PersonEntity:
          Name:
            NameFull: Iihara K
      – PersonEntity:
          Name:
            NameFull: Neumar R
      – PersonEntity:
          Name:
            NameFull: Nishimura K
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 11
              M: 06
              Text: 2021 Jun 11
              Type: published
              Y: 2021
          Identifiers:
            – Type: issn-electronic
              Value: 1468-201X
          Numbering:
            – Type: volume
              Value: 107
            – Type: issue
              Value: 13
          Titles:
            – TitleFull: Heart (British Cardiac Society)
              Type: main
ResultId 1