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Data Anonymization for Cloud-Based Storage of an Extensible Archive Format in Neurocritical Care

Gruen, V., Kenny, K., et al., Moyer, E.J.

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November 20, 2025

A Taxonomy for Defining Derived Metrics in Neurocritical Care for Machine Learning

Gruen, V., Kenny, K., et al., Moyer, E.J.

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November 20, 2025

Decision Support in Neurocritical Care Driven by Real-Time Physiology

Moyer, E.J., Maddux, C., et al., Moberg, D.

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November 20, 2025

CONNECT: A Platform for High-Resolution Multimodal Data Management for Clinical Trials of Brain Injured Patients

Moyer, E.J., Maddux, C., et al., Moberg, D.

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November 20, 2025

Harmonization of Physiological Data in Neurocritical Care: Challenges and a Path Forward

Elmer, J., He, Z., […], Hirsch, K.G., PRECICECAP Study Team

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November 20, 2025

Precision Care in Cardiac Arrest ICECAP (PRECICECAP) Study Protocol and Informatics Approach

Elmer, J., He, Z., […], Hirsch, K.G., PRECICECAP Study Team

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November 20, 2025

A Novel Annotation Tools Using Multimodality Neuromonitoring Data Superimposed with Clinically-Relevant Events for Machine Learning

Moyer, E.J., Kuoch, E., et al., Moberg, D.

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November 20, 2025

Semi-Automatic Pediatric Multimodal Neuromonitoring Reports

Moyer, E.J., Kuoch, E., et al., Moberg, D.

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November 20, 2025

Enhancing the Interoperability and AI Readiness of Neurocritical Care Data

Moyer, E.J., Lawrence, S., et al., Moberg, D.

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November 20, 2025

Moberg Analytics combines decades of experience in multimodal neuromonitoring, cloud technology, and AI to provide better care for acute brain-injured patients.

MCP is currently intended for research use only. The platform has not received FDA clearance or approval yet.

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