Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs

Autor: MILEA, D., NAJJAR, R. P., ZHUBO, J., TING, D., VASSENEIX, C., Xu, X., AGHSAEI FARD, M., FONSECA, P., VANIKIETI, K., LAGREZE, W. A., LA MORGIA, C., Cheung, C. Y., Hamann, S., Chiquet, C., SANDA, N., Yang, H., MEJICO, L. J., Rougier, Marie-Benedicte, KHO, R., THI HA CHAU, T., Singhal, S., GOHIER, P., CLERMONT-VIGNAL, C., CHENG, C. Y., JONAS, J. B., YU-WAI-MAN, P., FRASER, C. L., Chen, J. J., AMBIKA, S., MILLER, N. R., Liu, Y., NEWMAN, N. J., WONG, T. Y., BIOUSSE, V.

Publikováno v: New England Journal of Medicine
New England Journal of Medicine, Massachusetts Medical Society, 2020, 382 (18), pp.1687-1695. ⟨10.1056/NEJMoa1917130⟩

BackgroundNonophthalmologist physicians do not confidently perform direct ophthalmoscopy. The use of artificial intelligence to detect papilledema and other optic-disk abnormalities from fundus photographs has not been well studied.MethodsWe trained,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d46a982c60ffcbbc45c3525f48e2fdd2
https://hal.archives-ouvertes.fr/hal-03150966