Deep learning-based fully automatic Risser stage assessment model using abdominal radiographs.
| Published in: | Pediatric Radiology Vol. 54; no. 10; pp. 1692 - 1704 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Published: |
Springer Nature
Sep2024
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179460590&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179460590 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03010449 O03 jtl: Pediatric Radiology issn: 03010449 maglogo: N pubinfo: dt: Sep2024 vid: 54 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 179460590 178670283 10.1007/s00247-024-05999-1 179460590 ppf: 1692 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Deep learning-based fully automatic Risser stage assessment model using abdominal radiographs. aug: au: Hwang, Jae-Yeon Kim, Yisak Hwang, Jisun Suh, Yehyun Hwang, Sook Min Lee, Hyeyun Park, Minsu affil: https://ror.org/01z4nnt86 Department of Radiology, Seoul National University Hospital, 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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