View in EDS HTML Full Text PDF Full Text

Machine Learning Algorithm Accuracy Using Single- versus Multi-Institutional Image Data in the Classification of Prostate MRI Lesions.

Saved in:
Bibliographic Details
Title: Machine Learning Algorithm Accuracy Using Single- versus Multi-Institutional Image Data in the Classification of Prostate MRI Lesions.
Authors: Provenzano, Destie1, Melnyk, Oleksiy2, Imtiaz, Danish2, McSweeney, Benjamin2, Nemirovsky, Daniel2, Wynne, Michael2, Whalen, Michael2, Rao, Yuan James2, Loew, Murray1, Haji-Momenian, Shawn2, shajimomenian@mfa.gwu.edu
Source: Applied Sciences (2076-3417); Jan2023, Vol. 13 Issue 2, p1088, 14p
Database: Applied Science & Technology Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 161421504
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Machine Learning Algorithm Accuracy Using Single- versus Multi-Institutional Image Data in the Classification of Prostate MRI Lesions.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Provenzano%2C+Destie%22">Provenzano, Destie</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Melnyk%2C+Oleksiy%22">Melnyk, Oleksiy</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Imtiaz%2C+Danish%22">Imtiaz, Danish</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22McSweeney%2C+Benjamin%22">McSweeney, Benjamin</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Nemirovsky%2C+Daniel%22">Nemirovsky, Daniel</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Wynne%2C+Michael%22">Wynne, Michael</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Whalen%2C+Michael%22">Whalen, Michael</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Rao%2C+Yuan+James%22">Rao, Yuan James</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Loew%2C+Murray%22">Loew, Murray</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Haji-Momenian%2C+Shawn%22">Haji-Momenian, Shawn</searchLink><relatesTo>2</relatesTo>, <i>shajimomenian@mfa.gwu.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Applied+Sciences+%282076-3417%29%22">Applied Sciences (2076-3417)</searchLink>; Jan2023, Vol. 13 Issue 2, p1088, 14p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=161421504
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/app13021088
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 1088
    Titles:
      – TitleFull: Machine Learning Algorithm Accuracy Using Single- versus Multi-Institutional Image Data in the Classification of Prostate MRI Lesions.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Provenzano, Destie
      – PersonEntity:
          Name:
            NameFull: Melnyk, Oleksiy
      – PersonEntity:
          Name:
            NameFull: Imtiaz, Danish
      – PersonEntity:
          Name:
            NameFull: McSweeney, Benjamin
      – PersonEntity:
          Name:
            NameFull: Nemirovsky, Daniel
      – PersonEntity:
          Name:
            NameFull: Wynne, Michael
      – PersonEntity:
          Name:
            NameFull: Whalen, Michael
      – PersonEntity:
          Name:
            NameFull: Rao, Yuan James
      – PersonEntity:
          Name:
            NameFull: Loew, Murray
      – PersonEntity:
          Name:
            NameFull: Haji-Momenian, Shawn
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 01
              Text: Jan2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 20763417
          Numbering:
            – Type: volume
              Value: 13
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Applied Sciences (2076-3417)
              Type: main
ResultId 1