Keratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of op...
: To propose a deep-learning-based approach to automatically and objectively evaluate morphologic eyelid features using two-dimensional(2D) digital photographs and to assess the agreement between automatic and manual measurements.: The 2D photographs...
PURPOSE: Infiltration of activated dendritic cells and inflammatory cells in cornea represents an important marker for defining corneal inflammation. Deep transfer learning has presented a promising potential and is gaining more importance in compute...
Journal of refractive surgery (Thorofare, N.J. : 1995)
Apr 1, 2021
PURPOSE: To develop an artificial intelligence (AI) model to effectively assess local versus global progression of keratoconus using multiple tomographic parameters.
PURPOSE: To develop and compare deep learning (DL) algorithms to detect keratoconus on the basis of corneal topography and validate with visualization methods.
Fungal keratitis (FK) is the most devastating and vision-threatening microbial keratitis, but clinical diagnosis a great challenge. This study aimed to develop and verify a deep learning (DL)-based corneal photograph model for diagnosing FK. Corneal ...
Translational vision science & technology
Jun 18, 2020
PURPOSE: The purpose of this study was to establish a deep learning model for automated sub-basal corneal nerve fiber (CNF) segmentation and evaluation with in vivo confocal microscopy (IVCM).
Klinische Monatsblatter fur Augenheilkunde
Dec 5, 2019
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 develo...
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