| Literature DB >> 35641807 |
Richard Moberg1, Ethan Jacob Moyer2, DaiWai Olson3, Eric Rosenthal4, Brandon Foreman5.
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.Entities:
Keywords: Big data; Critical care; Data annotation; Informatics; Physiologic monitoring; Standards
Mesh：
Year: 2022 PMID： 35641807 DOI： 10.1007/s12028-022-01524-0
Source DB: PubMed Journal: Neurocrit Care ISSN： 1541-6933 Impact factor: 3.532