This project integrates multimodal eye data (CFP, OCT, OCTA) from 50,000 cases, brain MR data from 150,000 cases, and ICD diagnoses, medical orders, and test results from an eye-brain paired cohort of 8,000 cases to construct an eye-brain cross-modal mapping model and an eye-brain-systemic disease association model. It aims to clarify the quantitative associations between multimodal ocular features and brain structural and vascular characteristics as well as systemic disease ICD diagnoses, thereby uncovering the cross-organ and cross-modal linkage mechanisms between the eye and brain. Ultimately, it seeks to achieve mapping and prediction of brain imaging features based on ocular data, enable ocular-based diagnosis and prediction of various diseases, and contribute significantly to early disease screening, risk stratification, and optimization of clinical diagnosis and treatment.
Study Type
OBSERVATIONAL
Enrollment
208,000
No interventions were involved in this study.
Performance of Systemic Disease Prediction Models
Age- and sex-stratified Area Under the Receiver Operating Characteristic Curve (AUC)
Time frame: From the time of model construction and consistency alignment during the study period to the end of the 12-month follow-up after study initiation.
Model generalisation capability.
Evaluated by Cohen's kappa coefficient across external independent cohorts.
Time frame: From the completion of model construction and consistency calibration during the study period to the end of the 12-month follow-up after study initiation.
Eye-Brain Mapping Model Performance.
Measured by correlation coefficient between retinal imaging features and brain neuroimaging metrics.
Time frame: From the completion of model construction and consistency calibration during the study period to the end of the 12-month follow-up after study initiation.
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