Machine learning approach for hemorrhagic transformation prediction: capturing predictors` interaction

HIGHLIGHTS

• who: Ahmed F. Elsaid from the University Hospitals Leuven, Belgium Harvard Medical School, United States have published the paper: Machine learning approach for hemorrhagic transformation prediction: Capturing predictors` interaction, in the Journal: (JOURNAL)
• what: The aim of this study was to determine the incidence and predictors of HT, to evaluate predictor interaction, and to identify the best predicting models taking advantage of the state-of-the-art ML algorithms. Because the authors intended to split the sample into training and testing datasets and to compensate for any lost cases, the authors enrolled 360 participants, of . . .
  

   

  

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