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
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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
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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
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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
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