3 papers
q-bio.QM2026
Evaluating Deep Surrogate Models for Knee Joint Contact Mechanics Under Input-Limited Conditions
Zhengye Pan, Jianwei Zuo, Jiajia Luo
Background and Objective: Accurate surrogate modeling of knee joint contact mechanics is important for reconstructing stress distributions and identifying risk-relevant regions, ye…
q-bio.QM2026
Characterizing Long-Range Dependencies in Knee Joint Contact Mechanics: A Comparison of Topology Diffusion, Global Routing, and Hybrid Graph Neural Networks
Zhengye Pan, Jianwei Zuo, Jiajia Luo
Finite element analysis of knee joint contact mechanics is computationally expensive, which has motivated the development of graph neural network surrogate models. However, effecti…
q-bio.TO2026
Towards Structure-Aware Surrogate Modeling: Explicit Region Interaction Improves Knee Contact Stress Prediction
Zhengye Pan, Jianwei Zuo, Jiajia Luo
Knee contact-stress hotspots are closely linked to meniscal/cartilage injury risk. Still, high-fidelity subject-specific FEA is too computationally expensive for large-cohort, mult…