Synthetic Glaucoma Progression Dataset and Analysis Code for "ChatGPT-5–Assisted Nonlinear Time-Series Analysis of Glaucoma Progression

Exact synthetic dataset (300 patients / 600 eyes; ~5-year irregular follow-up) and analysis pipeline matching the manuscript “ChatGPT-5–Assisted Nonlinear Time-Series Analysis of Glaucoma Progression: Persistence, Volatility, and Rapid Deterioration Metrics from a Fully Synthetic Cohort”. The archive includes: Main dataset in CSV/XLSX format (exact version used in the manuscript) Data dictionary Per-eye metrics file used for results Preview subsets of the dataset Python script to reproduce per-eye metrics and Table 1 exactly as in the manuscript README with usage notes, license, and citation guidelines All data are fully synthetic and contain no personal health information (PHI).License: CC BY 4.0.Please cite both the manuscript and the dataset DOI when using this material.