Automated artificial intelligence‐based system for clinical follow‐up of patients with age‐related macular degeneration

Purpose In this study, we investigate the potential of a novel artificial intelligence‐based system for autonomous follow‐up of patients treated for neovascular age‐related macular degeneration (AMD). Methods A temporal deep learning model was trained on a data set of 84 489 optical coherence tomogr...

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Veröffentlicht in:	Acta ophthalmologica (Oxford, England) England), 2022-12, Vol.100 (8), p.927-936
Hauptverfasser:	Potapenko, Ivan, Thiesson, Bo, Kristensen, Mads, Hajari, Javad Nouri, Ilginis, Tomas, Fuchs, Josefine, Hamann, Steffen, la Cour, Morten
Format:	Artikel
Sprache:	eng
Schlagworte:	age‐related macular degeneration anti‐vegf Artificial Intelligence Consensus Decision making Deep learning Follow-Up Studies follow‐up Humans Macular degeneration Macular Degeneration - diagnosis Original Patients Tomography, Optical Coherence - methods Wet Macular Degeneration - diagnosis Wet Macular Degeneration - drug therapy
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