Predicting contrast sensitivity functions with digital twins

• Published in: Scientific reports Vol. 14; no. 1; pp. 24100 - 16
• Main Authors: Zhao, Yukai, Lesmes, Luis Andres, Dorr, Michael, Lu, Zhong-Lin
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 15.10.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 631/378/2613/2615; 639/705/1042; Accuracy; Adult; Bayes Theorem; Bayesian analysis; Clinical trials; Contrast Sensitivity - physiology; Contrast sensitivity function; Data collection; Digital twin; Digital twins; Female; Hierarchical Bayesian modeling; Humanities and Social Sciences; Humans; Male; Middle Aged; multidisciplinary; Precision medicine; Prediction; Predictions; Science; Science (multidisciplinary); Sensitivity analysis; Young Adult; Hierarchical Bayesian modeling; Digital twin; Contrast sensitivity function; Prediction

We developed and validated digital twins (DTs) for contrast sensitivity function (CSF) across 12 prediction tasks using a data-driven, generative model approach based on a hierarchical Bayesian model (HBM). For each prediction task, we utilized the HBM to compute the joint distribution of CSF hyperp...