Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.
| Publicado en: | European Radiology Vol. 34; no. 5; pp. 3431 - 3444 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2024
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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=177463555&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 177463555 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: May2024 vid: 34 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 177463555 173080414 10.1007/s00330-023-10306-x 177463555 ppf: 3431 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study. aug: au: Lee, Taehee Lee, Kyung Hee Lee, Jong Hyuk Park, Samina Kim, Young Tae Goo, Jin Mo Kim, Hyungjin affil: https://ror.org/01z4nnt86 Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, 03080, Seoul, South Korea sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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