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Machine Learning-Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review.

Sankavi MuralitharanWalter NelsonShuang DiMichael H McGillionPhilip J DevereauxNeil Grant BarrJeremy Petch
Published in: Journal of medical Internet research (2021)
In studies that compared performance, reported results suggest that machine learning-based early warning systems can achieve greater accuracy than aggregate-weighted early warning systems but several areas for further research were identified. While these models have the potential to provide clinical decision support, there is a need for standardized outcome measures to allow for rigorous evaluation of performance across models. Further research needs to address the interpretability of model outputs by clinicians, clinical efficacy of these systems through prospective study design, and their potential impact in different clinical settings.
Keyphrases
  • machine learning
  • clinical decision support
  • artificial intelligence
  • magnetic resonance
  • electronic health record
  • big data
  • human health
  • palliative care
  • risk assessment
  • climate change
  • contrast enhanced
  • case control