Predicting progression-free survival in sarcoma using MRI-based automatic segmentation models and radiomics nomograms: a preliminary multicenter study.
| Publicado en: | Skeletal Radiology Vol. 54; no. 7; pp. 1417 - 1428 |
|---|---|
| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jul2025
|
| 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=185156270&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 185156270 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03642348 O14 jtl: Skeletal Radiology issn: 03642348 maglogo: N pubinfo: dt: Jul2025 vid: 54 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 185156270 181404593 10.1007/s00256-024-04837-7 185156270 ppf: 1417 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Predicting progression-free survival in sarcoma using MRI-based automatic segmentation models and radiomics nomograms: a preliminary multicenter study. aug: au: Zhu, Nana Niu, Feige Fan, Shuxuan Meng, Xianghong Hu, Yongcheng Han, Jun Wang, Zhi affil: https://ror.org/02mh8wx89 Graduate School, Tianjin Medical University, Tianjin, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|