Detecting glaucoma from multi-modal data using probabilistic deep learning

OBJECTIVE: To assess the accuracy of probabilistic deep learning models to discriminate normal eyes and eyes with glaucoma from fundus photographs and visual fields. DESIGN: Algorithm development for discriminating normal and glaucoma eyes using data from multicenter, cross-sectional, case-control s...

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Detalles Bibliográficos
Autores principales: Huang, Xiaoqin, Sun, Jian, Gupta, Krati, Montesano, Giovanni, Crabb, David P., Garway-Heath, David F., Brusini, Paolo, Lanzetta, Paolo, Oddone, Francesco, Turpin, Andrew, McKendrick, Allison M., Johnson, Chris A., Yousefi, Siamak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556968/
https://www.ncbi.nlm.nih.gov/pubmed/36250081
http://dx.doi.org/10.3389/fmed.2022.923096

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556968/
https://www.ncbi.nlm.nih.gov/pubmed/36250081
http://dx.doi.org/10.3389/fmed.2022.923096

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