Prognostic value of deep learning–based fibrosis quantification on chest CT in idiopathic pulmonary fibrosis.
| Publicado en: | European Radiology Vol. 33; no. 5; pp. 3144 - 3156 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=163255749&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 163255749 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: May2023 vid: 33 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 163255749 162457966 10.1007/s00330-023-09534-y 163255749 ppf: 3144 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prognostic value of deep learning–based fibrosis quantification on chest CT in idiopathic pulmonary fibrosis. aug: au: Nam, Ju Gang Choi, Yunhee Lee, Sang-Min Yoon, Soon Ho Goo, Jin Mo Kim, Hyungjin affil: Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, 03080, Seoul, Republic of Korea sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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