Silvia S. Blemker

The paper extends a computational model of skeletal muscle regeneration to simulate and validate injury-specific responses to CTX, FI, and EC injuries, revealing distinct cytokine and cell dynamics across injury types.

This paper develops a multi-scale machine learning model to predict muscle and functional disease progression in FSHD using MRI and clinical data, achieving strong predictive performance in holdout datasets.

This study uses AI to analyze whole-body MRI scans, quantifying 71 muscles and 13 bones in healthy adults, revealing that skeletal size is a key determinant of muscularity.

The paper develops an agent-based model to simulate muscle regeneration, showing that combined cytokine parameter changes improve CSA recovery by 13%.

The paper validates the association between MRI characteristics and gene signatures in FSHD muscle, supporting their use as biomarkers for clinical trial design.