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Biorxiv : the Preprint Server for Biology|February 23, 2022
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-microbialsDale Larie, Gary An, Chase CockrellFrontiers in Immunology|December 8, 2022
Preparing for the next pandemic: Simulation-based deep reinforcement learning to discover and test multimodal control of systemic inflammation using repurposed immunomodulatory agentsChase Cockrell, Dale Larie, Gary AnFrontiers in Physiology|November 1, 2021
The Use of Artificial Neural Networks to Forecast the Behavior of Agent-Based Models of Pathophysiology: An Example Utilizing an Agent-Based Model of SepsisDale Larie, Gary An, R Chase CockrellMedrxiv : the Preprint Server for Health Sciences|January 30, 2023
Prediction of Long COVID Based on Severity of Initial COVID-19 Infection: Differences in predictive feature sets between hospitalized versus non-hospitalized index infectionsDamien Socia, Dale Larie, Sol Feuerwerker, et al.Surgery Open Science|October 11, 2023
Children are small adults (when properly normalized): Transferrable/generalizable sepsis predictionCaitlin Marassi, Damien Socia, Dale Larie, et al.Gait & Posture|July 3, 2020
Metrics extracted from a single wearable sensor during sit-stand transitions relate to mobility impairment and fall risk in people with multiple sclerosisLindsey J Tulipani, Brett Meyer, Dale Larie, et al.IEEE Journal of Biomedical and Health Informatics|September 18, 2020
Wearables and Deep Learning Classify Fall Risk From Gait in Multiple SclerosisBrett M Meyer, Lindsey J Tulipani, Reed D Gurchiek, et al.Tissue Engineering. Part A|August 30, 2022
Transcriptomic, Proteomic, and Morphologic Characterization of Healing in Volumetric Muscle LossRaphael J Crum, Scott A Johnson, Peng Jiang, et al.Pageof 1