Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.

Saved in:
Bibliographic Details
Title: Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.
Authors: Wu HY; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China., Li ZG; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China., Sun XK; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China., Bai WM; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China., Wang AD; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China., Ma YC; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China., Diao RH; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China., Fan EY; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China., Zhao F; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China., Liu YQ; Nanjing Foreign Language School, Nanjing, Jiangsu, People's Republic of China., Hong YZ; Nanjing Foreign Language School, Nanjing, Jiangsu, People's Republic of China., Guo MH; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China. guominghua66@sina.com., Xue H; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China. hxue@seu.edu.cn., Liang WB; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China. wenbiaoliang@hotmail.com.
Source: Scientific reports [Sci Rep] 2022 Nov 10; Vol. 12 (1), pp. 19165. Date of Electronic Publication: 2022 Nov 10.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep 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: 36357435
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Wu+HY%22">Wu HY</searchLink>; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Li+ZG%22">Li ZG</searchLink>; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Sun+XK%22">Sun XK</searchLink>; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Bai+WM%22">Bai WM</searchLink>; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Wang+AD%22">Wang AD</searchLink>; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Ma+YC%22">Ma YC</searchLink>; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Diao+RH%22">Diao RH</searchLink>; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Fan+EY%22">Fan EY</searchLink>; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Zhao+F%22">Zhao F</searchLink>; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Liu+YQ%22">Liu YQ</searchLink>; Nanjing Foreign Language School, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Hong+YZ%22">Hong YZ</searchLink>; Nanjing Foreign Language School, Nanjing, Jiangsu, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Guo+MH%22">Guo MH</searchLink>; Yangzhou Blood Station, Yangzhou, Jiangsu, People's Republic of China. guominghua66@sina.com.<br /><searchLink fieldCode="AU" term="%22Xue+H%22">Xue H</searchLink>; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, People's Republic of China. hxue@seu.edu.cn.<br /><searchLink fieldCode="AU" term="%22Liang+WB%22">Liang WB</searchLink>; Jiangsu Province Blood Center, Nanjing, Jiangsu, People's Republic of China. wenbiaoliang@hotmail.com.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101563288%22">Scientific reports</searchLink> [Sci Rep] 2022 Nov 10; Vol. 12 (1), pp. 19165. <i>Date of Electronic Publication: </i>2022 Nov 10.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article; Research Support, Non-U.S. Gov't
– 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>101563288 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2045-2322 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220452322%22">20452322 </searchLink><i>NLM ISO Abbreviation: </i>Sci Rep <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=36357435
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1038/s41598-022-21215-2
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 19165
    Titles:
      – TitleFull: Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wu HY
      – PersonEntity:
          Name:
            NameFull: Li ZG
      – PersonEntity:
          Name:
            NameFull: Sun XK
      – PersonEntity:
          Name:
            NameFull: Bai WM
      – PersonEntity:
          Name:
            NameFull: Wang AD
      – PersonEntity:
          Name:
            NameFull: Ma YC
      – PersonEntity:
          Name:
            NameFull: Diao RH
      – PersonEntity:
          Name:
            NameFull: Fan EY
      – PersonEntity:
          Name:
            NameFull: Zhao F
      – PersonEntity:
          Name:
            NameFull: Liu YQ
      – PersonEntity:
          Name:
            NameFull: Hong YZ
      – PersonEntity:
          Name:
            NameFull: Guo MH
      – PersonEntity:
          Name:
            NameFull: Xue H
      – PersonEntity:
          Name:
            NameFull: Liang WB
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 10
              M: 11
              Text: 2022 Nov 10
              Type: published
              Y: 2022
          Identifiers:
            – Type: issn-electronic
              Value: 2045-2322
          Numbering:
            – Type: volume
              Value: 12
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Scientific reports
              Type: main
ResultId 1