Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.

Bibliographic Details
Published in:European Radiology Vol. 30; no. 8; pp. 4595 - 4606
Main Authors: Wang, Xinhui, Wan, Qi, Chen, Houjin, Li, Yanfeng, Li, Xinchun
Format: Journal Article
Published: Springer Nature Aug2020
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=144404675&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 144404675
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        09387994
        NPH
      jtl: European Radiology
      issn: 09387994
      maglogo: N
    pubinfo:
      dt: Aug2020
      vid: 30
      iid: 8
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        144404675
        144076405
        10.1007/s00330-020-06768-y
        144404675
      ppf: 4595
      ppct: 11
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
      aug:
        au:
          Wang, Xinhui
          Wan, Qi
          Chen, Houjin
          Li, Yanfeng
          Li, Xinchun
        affil: School of Electronic and Information Engineering, Beijing Jiaotong University, Shangyuan Village No 3 in Haidian, Beijing, China
      sug:
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
      ab:
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N