ARVO 2018 Presentations

Automated identification of disease activity and therapeutic response in neovascular AMD by deep learning

Ursula Schmidt-Erfurth, Wolf-Dieter Vogl, Sebastian Waldstein, Bianca S. Gerendas, Thomas Schlegl, Hrvoje Bogunovic


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Artificial intelligence to predict optimal treatment intervals in treat-and-extend (T&E)

Hrvoje Bogunovic, Sebastian Waldstein, Amir Sadeghipour, Bianca S. Gerendas, Ursula Schmidt-Erfurth

Abstract DOWNLOAD >>




ARVO 2018 Posters

Unsupervised deep learning to identify markers in OCT of AMD

Sebastian M. Waldstein*, Philipp Seeböck*, Rene Donner, Bianca S. Gerendas, Amir Sadeghipour, Georg Langs, Aaron Osborne, Ursula Schmidt-Erfurth

 *contributed equally



Predicting Visual Acuity Outcomes in nAMD, RVO and DME by Machine Learning

Amir Sadeghipour, Sebastian M. Waldstein, Bianca S. Gerendas, Aaron Osborne, Ursula Schmidt-Erfurth




Influence of posterior vitreous detachment on extendability of treat-and-extend anti-VEGF therapy in neovascular age-related macular degeneration

Sophie Klimscha, Léon Coulibaly, Amir Sadeghipour, Bianca S. Gerendas, Sebastian M. Waldstein, Ursula Schmidt-Erfurth