C. Cockrell

The Wound Environment Agent-based Model (WEABM): a digital twin platform for characterization and complex therapeutic discovery for volumetric muscle loss

This paper develops a digital twin platform, WEABM, to model VML healing and discover therapeutic strategies through simulation-based reinforcement learning.

Preparing for the next COVID: Deep Reinforcement Learning trained Artificial Intelligence discovery of multi-modal immunomodulatory control of systemic inflammation in the absence of effective anti-microbials

This paper uses deep reinforcement learning to discover immunomodulatory strategies for controlling systemic inflammation in the absence of effective anti-microbials, reducing mortality from 85% to 10.4% in simulations.

Quantifying the size and healing of volumetric muscle wounds using 3D Slicer on CT scans in a canine model

The paper presents a method to quantify volumetric muscle wound size and healing using 3D Slicer on CT scans in a canine model.

Comparative computational modeling of the bat and human immune response to viral infection with the Comparative Biology Immune Agent Based Model

This study develops a computational model to compare bat and human immune responses to viral infection, highlighting differences in inflammasome activity and Type 1 Interferon dynamics that contribute to viral tolerance.

Optimization of Dose Schedules for Chemotherapy of Early Colon Cancer Determined by High Performance Computer Simulations

This study uses computer simulations to identify optimal chemotherapy dose schedules for early colon cancer by evaluating parameters like duration, interval, and lethality.