A systematic review of AI for predicting glaucoma progression: challenges and recommendations towards clinical implementation.
| Publicado en: | NPJ Digital Medicine Vol. 9; no. 1; pp. 1 - 19 |
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| Autores principales: | , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Springer Nature
1/22/2026
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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=191451161&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191451161 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23986352 LQV4 jtl: NPJ Digital Medicine issn: 23986352 maglogo: N pubinfo: dt: 1/22/2026 vid: 9 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 191451161 191451161 191451161 10.1038/s41746-025-02321-7 191451161 ppf: 1 ppct: 18 formats: tig: atl: A systematic review of AI for predicting glaucoma progression: challenges and recommendations towards clinical implementation. aug: au: Liang, Yichuan G. Fan, Leo Teixeira-Pinto, Armando Liew, Gerald White, Andrew J. R. affil: https://ror.org/0384j8v12 Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia sug: subj: Glaucoma Risk Factors Disease Progression Risk Factors Risk Assessment Diagnosis, Computer Assisted Artificial Intelligence Predictive Value of Tests Implementation Science Human Systematic Review Medline Embase Cochrane Library Descriptive Statistics Confidence Intervals Funding Source pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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