Artificial intelligence (AI) is gaining widespread traction in ophthalmology, with multiple screening and diagnostic tools already being approved by U. S. and EU authorities. However, the adoption of these tools among medical professionals and their ...
Klinische Monatsblatter fur Augenheilkunde
Dec 5, 2024
Recent years have seen formidable advances in artificial intelligence. Developments include a large number of specialised systems either existing or planned for use in scientific research, data analysis, translation, text production and design with g...
Artificial intelligence (AI) has already found its way into ophthalmology, with the first approved algorithms that can be used in clinical routine. Retinal diseases in particular are proving to be an important area of application for AI, as they are ...
Endothelial cell density (ECD) is a crucial parameter for the release of corneal grafts for transplantation. The Lions Eye Bank of Baden-Württemberg uses the "Rhine-Tec Endothelial Analysis System" for ECD quantification, which is based on a fixed co...
Klinische Monatsblatter fur Augenheilkunde
Mar 19, 2024
The training of artificial intelligence (AI) is becoming increasingly popular. More and more studies on lamellar keratoplasty are also being published. In particular, the possibility of non-invasive and high-resolution imaging technology of optical c...
Despite the advantages that robot-assisted surgery can offer to patient care, its use in ophthalmic surgery has not yet progressed to the extent seen in other fields. As such, its use remains limited to research environments, both basic and clinical....
Klinische Monatsblatter fur Augenheilkunde
Nov 23, 2020
BACKGROUND AND PURPOSE: In the last decade, artificial intelligence and machine learning algorithms have been more and more established for the screening and detection of diseases and pathologies, as well as for describing interactions between measur...
Klinische Monatsblatter fur Augenheilkunde
Nov 19, 2020
Medical images play an important role in ophthalmology and radiology. Medical image analysis has greatly benefited from the application of "deep learning" techniques in clinical and experimental radiology. Clinical applications and their relevance fo...