Clinical Prediction Performance of Glaucoma Progression Using a 2-Dimensional Continuous-Time Hidden Markov Model with Structural and Functional Measurements

Previously, we introduced a state-based 2-dimensional continuous-time hidden Markov model (2D CT HMM) to model the pattern of detected glaucoma changes using structural and functional information simultaneously. The purpose of this study was to evaluate the detected glaucoma change prediction performance of the model in a real clinical setting using a retrospective longitudinal dataset.

Source: Ophthalmology - March 20, 2018 Category: Opthalmology Authors: Youngseok Song, Hiroshi Ishikawa, Mengfei Wu, Yu-Ying Liu, Katie A. Lucy, Fabio Lavinsky, Mengling Liu, Gadi Wollstein, Joel S. Schuman Source Type: research