Prediction model of preeclampsia using machine learning based methods: a population based cohort study in china

HIGHLIGHTS

• What: COPYRIGHT and This is an open-access Article use distribution or reproduction in other forums is permitted provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited in accordance with accepted academic practice. The models provide an accessible tool for large-scale population screening and prediction of preeclampsia, which helps reduce the disease burden and improve maternal and fetal outcomes. The authors develop predictive models for PE using new ML techniques such as the Extra Trees Classifier (ETC), Voting Classifier (VC), Gaussian Process Classifier . . .
  

   

  

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