Application of machine learning techniques in the diagnosis of endometriosis.
| Published in: | BMC Women's Health Vol. 24; no. 1; pp. 1 - 10 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Published: |
BioMed Central
9/5/2024
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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=179459507&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179459507 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14726874 1CIP jtl: BMC Women's Health issn: 14726874 maglogo: N pubinfo: dt: 9/5/2024 vid: 24 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 179459507 10.1186/s12905-024-03334-2 179459507 ppf: 1 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Application of machine learning techniques in the diagnosis of endometriosis. aug: au: Zhao, Ningning Hao, Ting Zhang, Fengge Ni, Qin Zhu, Dan Wang, Yanan Shi, Yali Mi, Xin affil: https://ror.org/04skmn292 Department of Obstetrics and Gynecology, Shunyi Women's and Children's Hospital of Beijing Children's Hospital, No. 1 of shun Hong Road, Shunyi District, 101300, Beijing, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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