Development of a deep-learning algorithm for etiological classification of subarachnoid hemorrhage using non-contrast CT scans.
| Publicado en: | European Radiology Vol. 35; no. 11; pp. 6775 - 6785 |
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| Autores principales: | , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2025
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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=188901889&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188901889 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Nov2025 vid: 35 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 188901889 187454732 10.1007/s00330-025-11666-2 188901889 ppf: 6775 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Development of a deep-learning algorithm for etiological classification of subarachnoid hemorrhage using non-contrast CT scans. aug: au: Chen, Lingxu Wang, Xiaochen Li, Yuanjun Bao, Yang Wang, Sihui Zhao, Xuening Yuan, Mengyuan Kang, Jianghe Sun, Shengjun affil: https://ror.org/013xs5b60 Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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