Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records

This research validates a deep learning algorithm for glaucoma risk assessment using systemic electronic health records. The model, fine-tuned on Stanford patient data, achieved an AUROC of 0.883 and PPV of 0.657, showing strong potential for scalable and accessible pre-screening.