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Development and external validation of a stability machine learning model to identify wake-up stroke onset time from MRI.

Liang JiangSiyu WangZhongping AiTingwen ShenHong ZhangShaofeng DuanYu-Chen ChenXin-Dao YinJun Sun
Published in: European radiology (2022)
• Machining learning model helps clinicians to identify wake-up stroke patients within 4.5 h of symptom onset. • A prospective study showed that svmRadial model based on DWI + FLAIR was the most stable in predicting the stroke onset time. • External validation showed that svmRadial model has good generalization ability in predicting the stroke onset time.
Keyphrases
  • machine learning
  • atrial fibrillation
  • magnetic resonance imaging
  • palliative care
  • magnetic resonance
  • artificial intelligence
  • big data
  • diffusion weighted