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ABSTRACT: Background
Modern clinical care in intensive care units is full of rich data, and machine learning has great potential to support clinical decision-making. The development of intelligent machine learning-based clinical decision support systems is facing great opportunities and challenges. Clinical decision support systems may directly help clinicians accurately diagnose, predict outcomes, identify risk events, or decide treatments at the point of care.Objective
We aimed to review the research and application of machine learning-enabled clinical decision support studies in intensive care units to help clinicians, researchers, developers, and policy makers better understand the advantages and limitations of machine learning-supported diagnosis, outcome prediction, risk event
SUBMITTER: Hong N
PROVIDER: S-EPMC8931648 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature