Abstract
Continuous multimodal monitoring in neurocritical care provides valuable insights into the dynamics of the injured brain. Unfortunately, the “readiness” of this data for robust artificial intelligence (AI) and machine learning (ML) applications is low and presents a significant barrier for advancement. Harmonization standards and tools to implement those standards are key to overcoming existing barriers. Consensus in our professional community is essential for success.
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Supported by the US Army (W81XWH1920013 to Moberg Analytics, Inc.; Richard Moberg, principal investigator).
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Richard Moberg is employed by and has ownership in Moberg Analytics, Inc. Ethan Moyer is employed at Moberg Analytics, Inc. DaiWai Olson is the editor for the Journal of Neuroscience Nursing and has received consulting fees from Moberg Analytics, Inc. Eric Rosenthal received speaking fees and consulting fees from UCB, Inc. Brandon Foreman received speaking fees and consulting fees from UCB, Inc.
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Moberg, R., Moyer, E.J., Olson, D. et al. Harmonization of Physiological Data in Neurocritical Care: Challenges and a Path Forward. Neurocrit Care 37 (Suppl 2), 202–205 (2022). https://doi.org/10.1007/s12028-022-01524-0
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DOI: https://doi.org/10.1007/s12028-022-01524-0