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Predicting Functional Outcome Using 24-Hour Post-Treatment Characteristics: Application of Machine Learning Algorithms in the STRATIS Registry.

Alicia C CastonguayZeinab ZoghiOsama O ZaidatRichard E BurgessSyed F ZaidiNils Mueller-KronastDavid S LiebeskindMouhammad A Jumaa
Published in: Annals of neurology (2022)
In this substudy, we found similar predictive accuracy for functional outcome when using the 24-hour NIHSS score as a continuous or dichotomous variable in ML models. ML models had moderate-to-good predictive accuracy, with RF outperforming LR models. External validation of these ML models is warranted. ANN NEUROL 2022.
Keyphrases
  • machine learning
  • blood pressure
  • deep learning
  • artificial intelligence
  • big data