Application of machine learning techniques in GlaucomAI system for glaucoma diagnosis and collaborative research support.

This paper proposes an architecture of the system that provides support for collaborative research focused on analysis of data acquired using Triggerfish contact lens sensor and devices for continuous monitoring of cardiovascular system properties. The system enables application of machine learning (ML) models for glaucoma diagnosis without direct intraocular pressure measurement and independently of complex imaging techniques used in clinical practice. We describe development of ML models based on sensor data and measurements of corneal biomechanical properties.