Using machine learning to classify human fetal health and analyze feature importance

HIGHLIGHTS

  • who: Yiqiao Yin and Yash Bingi from the Department of Statistics, Columbia University, New York, NY, USA have published the article: Using Machine Learning to Classify Human Fetal Health and Analyze Feature Importance, in the Journal: Biomedinformatics 2023, 3, 280-298. of /2023/
  • what: Using a support vector machine (SVM) and oversampling this paper proposes a model that classifies fetal health with an accuracy of 99.59%. If the model was to predict a pathological case for a fetus, it would also be able to show that the reason behind the prediction was a low . . .

     

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