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Moberg Analytics is authoring ground-breaking research and publications with some of the top neurocritical care institutions, physicians, nurses, and researchers.

Moberg Analytics Research & Publications

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A Cloud-Based Platform for Data Management in Traumatic Brain Injury Clinical Trials (CONNECT): Progress from the MIND Workgroup

Stover, J., Maddux, C., et al., Moberg, D.

A Multimodal Monitoring Approach to Predicting Onset of Physiological Incidents Using Machine Learning

Moyer, E.J., Isozaki, I., Moberg, D.

A Multimodal Monitoring Approach to Predicting Onset of Physiological Incidents Using Machine Learning

Moyer, E.J., Isozaki, I., Moberg, D.

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.

A Robust Data Archive Format for Traumatic Brain Injury Physiology and Machine Learning: Progress from the MIND Workgroup

Sharma, G., Nooney, S., et al., Rosenthal, E.S.

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

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

Advancing InTBIR's Goals: A Platform for Large0Scale Physiological Data Analytics

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

Assessing the Clinical Value and Deployability of TBI Monitoring Technology for Prolonged Casualty Care

Gomba, M.A., Moyer, E.J., et al., Moberg, D.

Challenges and Opportunities in Multimodal Monitoring and Data Analytics in Traumatic Brain Injury

Foreman, B., Lissak, I.A., et al., Rosenthal, E.S.

Comparison of NIRS-derived MAPopt Between ICM+ and Moberg Analytics in Pediatric Post-Cardiac Arrest Patients.

Moyer, E.J., Moberg, R., et al., Keenan, S.

Comparison of NIRS-derived MAPopt Between ICM+ and Moberg Analytics in Pediatric Post-Cardiac Arrest Patients.

Moyer, E.J., Moberg, R., et al., Keenan, S.

Comparison of NIRS-Derived MAPopt Between Moberg Analytics and ICM+ in Pediatric Post-Cardiac Arrest Patients

Moore, J., Moyer, E.J., et al., Kirschen, M.

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.

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

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

Decision Support in Neurocritical Care Driven by Real-Time Physiology

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

Development and Validation of an Open-Source Optimum Cerebral Perfusion Pressure Tool to Guide Precision Care in Every Traumatic Brain Injury

Sharma, G., Olson, D.M., et al., Rosenthal, E.S.

Development and Validation of an Open-Source, Online Optimum Cerebral Perfusion Pressure Tool to Guide Precision are in Severe Traumatic Brain Injury: Progress for the MIND Workgroup

Foreman, B., Li, F., et al., Moberg, D.

Development of a TBI Navigator: Multimodal Assessment and Monitoring to Enhance TBI Management in Role 1 of Care.

Moyer, E.J., Moberg, R., et al., Keenan, S.

Development of the Autonomous Communications Medical Ecosystem (ACME): A Multimodal Sensor Suite for Passive Data Collection During Combat Casualty Care.

Moyer, E.J., Moberg, R., et al., Keenan, S.

Enhancing the Interoperability and AI Readiness of Neurocritical Care Data

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

Extracting Meaning from Neurocritical Care Annotations Requires a Brain Injury-Specific Natural Language Processing Vocabulary: Progress from the MIND Workgroup

Sharma, G., Olson, D.M., et al., Rosenthal, E.S.

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

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

Integration of High-Resolution Multimodal Neuromonitoring Data and Hospital EMR for Automated Near Real-Time Patient Care Reports

Maddux, C., Kirschen, M., et al., Moberg, D.

Methodology of Measuring the Precise Temporal-Spatial Behavior of Electrographic Seizures in Full Term Newborns with Arterio-Ischemic Strokes

Fung, F., Moyer, E.J., et al., Clancy, R.R.

MIND Collaborative Effort to Developing Meaning from Annotated Data During Continuous Multimodal Monitoring

Foreman, B., Lissak, I.A., et al., Rosenthal, E.S.

Pitfalls and Possibilities of Using Root SedLine for Continuous Assessment of EEG Waveform-Based Metrics in Intensive Care Research

Bögli, S.Y., Cherchi, M.S., et al., Smielewski, P.

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

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

Predicting the Trajectory of Intracranial Pressure in Patients with Traumatic Brain Injury: Evaluation of a Foundation Model for Time Series

Van Leeuwen, F.D., Bhattacharyay, S., et al., Moberg, R.

Semi-Automatic Pediatric Multimodal Neuromonitoring Reports

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

The Development of a TBI Navigator to Augment Management of Brain Injured Patients in Austere Environments

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

The Severity and Persistence of Neurological Deterioration are Associated with Clinical Outcome: Progress from the MIND Workgroup

Sharma, G., Nooney, S., et al., Rosenthal, E.S.

Towards the Management of Ground Truth Consensus-Based Knowledge in Neurocritical Care

Maddux, C., Kirschen, M., et al., Moberg, D.

Using Contextual Data to Enhance Machine Learning in Traumatic Brain Injury

Goldblum, Z., Olson, D., et al., Moberg, D.

Using Physiological Biomarkers to Optimize Management of TBI in Austere Environments

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