[Artificial Intelligence for the Development of Screening Parameters in the Field of Corneal Biomechanics].

Machine learning and artificial intelligence are mostly important if data analysis by knowledge-based analytical methods is difficult and complex. In such cases, combined analytical and empirical approaches based on AI are also meaningful. The development and validation of several clinical parameters for the Corvis ST are a concrete example of this approach. In this article, the development of three screening parameters is described. It is shown how these developments lead to clinical solutions that can be beneficial for detecting clinical and subclinical keratoconus as well as for glaucoma screening.