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Predicting Hypoxia Using Machine Learning: Systematic Review.

Lena PigatBenjamin P GeislerSeyedmostafa SheikhalishahiJulia SanderMathias KasparMaximilian SchmutzSven Olaf RohrCarl Mathis WildSebastian GossSarra ZaghdoudiLudwig Christian Hinske
Published in: JMIR medical informatics (2024)
Machine learning models provide the potential to accurately predict the occurrence of hypoxic events based on retrospective data. The heterogeneity of the studies and limited generalizability of their results highlight the need for further validation studies to assess their predictive performance.
Keyphrases
  • systematic review
  • machine learning
  • case control
  • big data
  • meta analyses
  • risk assessment
  • single cell
  • artificial intelligence
  • endothelial cells
  • climate change
  • data analysis