Artificial intelligence to detect papilledema from ocular fundus photographs
ContributorsMilea, Dan; Najjar, Raymond P.
; Jiang, Zhubo; Ting, Daniel; Vasseneix, Caroline; Xu, Xinxing; Aghsaei Fard, Masoud; Fonseca, Pedro; Vanikieti, Kavin; Lagrèze, Wolf A.; La Morgia, Chiara; Cheung, Carol Y.; Hamann, Steffen; Chiquet, Christophe; Sanda, Nicolae; Yang, Hui; Mejico, Luis J.; Rougier, Marie-Bénédicte; Kho, Richard; Tran, Thi H.C.
; Singhal, Shweta; Gohier, Philippe; Clermont-Vignal, Catherine; Cheng, Ching-Yu; Jonas, Jost B.; Yu-Wai-Man, Patrick; Fraser, Clare L.; Chen, John J.; Ambika, Selvakumar; Miller, Neil R.; Liu, Yong; Newman, Nancy J.; Wong, Tien Y.; Biousse, Valérie; BONSAI Group
CollaboratorsThumann, Gabriele
Published inNew England Journal of Medicine, vol. 382, no. 18, p. 1687-1695
Publication date2020
Abstract
Keywords
- DIABETIC-RETINOPATHY
- EMERGENCY
- OPHTHALMOSCOPY
- FEASIBILITY
- VALIDATION
- HEADACHE
- CAMERA
Affiliation entities
Research groups
Citation (ISO format)
MILEA, Dan et al. Artificial intelligence to detect papilledema from ocular fundus photographs. In: New England Journal of Medicine, 2020, vol. 382, n° 18, p. 1687–1695. doi: 10.1056/NEJMoa1917130
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Article (Published version)
Secondary files (1)
Appendix
Identifiers
- PID : unige:155363
- DOI : 10.1056/NEJMoa1917130
- PMID : 32286748
Additional URL for this publicationhttp://www.nejm.org/doi/10.1056/NEJMoa1917130
Journal ISSN0028-4793
