Diagnostik von Erkrankungen des Sehnervenkopfes in Zeiten von künstlicher Intelligenz und Big Data

BACKGROUND: The use of artificial intelligence (AI) interesting for automated image segmentation, analysis and classification, among others and has already been described for various fields of ophthalmology. OBJECTIVE: This manuscript provides an overview of current approaches and advances in the application of big data and AI in various diseases of the optic nerve head. MATERIAL AND METHODS: A PubMed search was performed. Studies were searched for that answered clinical questions using big data approaches or classical machine learning methods in the analysis of multimodal imaging of the optic nerve head. RESULTS: Big data can help to answer clinical questions in common diseases such as glaucoma. The AI is applied for the segmentation of multimodal imaging of the optic nerve head as well as for the classification of diseases, such as glaucoma or optic disc edema on this imaging data. CONCLUSION: With the help of big data and AI, relationships can be recognized more easily and the diagnostics and course assessment of diseases of the optic nerve head can be facilitated or automated. A prerequisite for clinical application is a CE marking as a medical device in Europe and approval by the Food and Drug Administration in the USA.