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Table 3 The performance of accuracy and precision in six models to predict threatened miscarriage

From: Construction of machine learning tools to predict threatened miscarriage in the first trimester based on AEA, progesterone and β-hCG in China: a multicentre, observational, case-control study

Models

Accuracy (95% CI)

Precision (95% CI)

KNN

0.60 (0.52–0.67)

0.57 (0.45–0.72)

LR

0.65 (0.50–0.78)

0.70 (0.48–0.98)

SVM

0.62 (0.52–0.72)

0.68 (0.48–0.89)

RF

0.64 (0.46–0.79)

0.63 (0.44-0.81)

MLP

0.62 (0.56–0.74)

0.61 (0.50–0.87)

XGboost

0.64 (0.50–0.77)

0.61 (0.47–0.79)

  1. KNN k-nearest neighbors classifier, LR Logistic regression, SVM Support vector machine, RF Random forest, MLP Multilayer perceptron, 95% CI 95% confidence interval
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BMC Pregnancy and Childbirth

ISSN: 1471-2393

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