Simulation-based inference for subject-specific tuning of middle ear finite-element models towards personalized objective diagnosis.

ABSTRACT: Computational models, particularly finite-element (FE) models, are essential for interpreting experimental data and predicting system behavior, especially when direct measurements are limited. Tuning these models is particularly challenging when a large number of parameters are involved. Traditional methods, such as sensitivity analyses, are time-consuming and often provide only a single set of parameter values, focusing on reproducing averaged trends rather than capturing experimental variability. New approaches are needed to make computational models more adaptable to patient-specific clinical applications. We applied simulation-based inference (SBI) using neural posterior estimation (NPE) to tune an FE model of the human middle ear against subject-specific data. The training dataset con

SUBMITTER: Motallebzadeh H 

PROVIDER: S-EPMC12583476 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature