We identified 298 metabolites in pseudoexfoliation (PEX) glaucoma, primary open angle glaucoma (POAG) and non-glaucomatous controls. Machine learning can classify aqueous humor into the three distinct categories and presents the opportunity for future predictions.
Abstract
Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.
Machine learning approach for intraocular disease prediction based on aqueous humor immune mediator profiles
