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Utilizing imaging parameters for functional outcome prediction in acute ischemic stroke: A machine learning study.

Burak Berksu OzkaraMert KarabacakMeisam HoseinyazdiSamir A DagherRichard C WangSadik Y KaradonF Eymen UcisikKonstantinos MargetisYing LiVivek Srikar Yedavalli
Published in: Journal of neuroimaging : official journal of the American Society of Neuroimaging (2024)
Using only imaging parameters, our model had an AUROC of 0.91 which was superior to most previous studies, indicating that imaging parameters may be as accurate as conventional predictors. The multiphase CTA collateral score was the most predictive variable, highlighting the importance of collaterals.
Keyphrases
  • high resolution
  • machine learning
  • artificial intelligence
  • big data
  • photodynamic therapy