Automatic image segmentation and online survival prediction model of medulloblastoma based on machine learning.
| Publicado en: | European Radiology Vol. 34; no. 6; pp. 3644 - 3656 |
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| Autores principales: | , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2024
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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=177797462&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 177797462 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Jun2024 vid: 34 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 177797462 173795317 10.1007/s00330-023-10316-9 177797462 ppf: 3644 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automatic image segmentation and online survival prediction model of medulloblastoma based on machine learning. aug: au: Zhou, Lili Ji, Qiang Peng, Hong Chen, Feng Zheng, Yi Jiao, Zishan Gong, Jian Li, Wenbin affil: https://ror.org/013xs5b60 Cancer Center, Beijing Tiantan Hospital, Capital Medical University, No. 119, Nansihuan West Road, Fengtai District, 100070, Beijing, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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