Artificial Intelligence (AI) is revolutionizing visual health by introducing personalized, data-driven approaches to diagnosis and rehabilitation. In orthoptics, AI-based systems can analyze ocular motility, vergence stability, fixation dynamics, and binocular coordination to design individualized rehabilitation protocols that adapt in real time to a patient’s performance and neural feedback.
This presentation introduces Orthocare, an AI-assisted digital platform that integrates classical orthoptic methods with machine learning algorithms to monitor visual function, detect anomalies, and optimize rehabilitation outcomes. Early clinical observations indicate that AI-guided visual training significantly improves convergence control, oculomotor precision, and cortical activation, suggesting enhanced neuroplastic adaptation.
The study also discusses how AI models can predict therapeutic progress and personalize the sequence and intensity of exercises, promoting more efficient visuo-motor and visuo-cognitive recovery.
By merging clinical orthoptics and artificial intelligence, Orthocare illustrates the future of neurovisual rehabilitation one that is intelligent, adaptive, and accessible across diverse healthcare contexts.