Surrogate Modeling

Ensemble Learning-Based Surrogate Models for Non-Invasive Estimation of Corneal Mechanical Properties
Random Forest, XGBoost, and LightGBM surrogate models predict third-order Ogden corneal parameters from apex displacement data, evaluated with a physics-informed stress-stretch metric.
Seyed Sadjad Abedi-Shahri, Mitra Baradari, Iman Zoljanahi Oskui
Cite
ICBME 2025 - Oral Presentation 2
Oral Presentation in 32nd National Conference and the 10th International Conference on Iranian Biomedical Engineering on Ensemble Learning-Based Surrogate Models for Non-Invasive Estimation of Corneal Mechanical Properties
Nov 20, 2025 Tabriz University of Technology
Seyed Sadjad Abedi-Shahri, Mitra Baradari, Iman Zoljanahi Oskui
ICBME 2025 - Oral Presentation 2