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Table 3 Classification results of the prospective study

From: Automated prediction of early spontaneous miscarriage based on the analyzing ultrasonographic gestational sac imaging by the convolutional neural network: a case-control and cohort study

Methods

Characteristics

Accuracy,% (95%CI)

Sensitivity,% (95%CI)

Specificity,% (95%CI)

PPV,% (95%CI)

NPV,% (95%CI)

AUC (95%CI)

CNN

VGG19

78.10 (76.21, 79.99)

80.39 (78.59, 82.18)

94.52 (89.15, 99.88)

94.89 (89.85, 99.88)

77.00(75.27, 78.72)

0.885 (0.846, 0.925)

ultrasound characteristics

CRL

66.34 (56.65, 74.82)

66.67 (29.57, 90.75)

66.32 (56.32, 75.04)

11.11 (3.82, 25.91)

96.92 (88.83, 99.78)

0.665 (0.564–0.756)

HR

82.18 (73.49, 88.51)

50.00 (18.76, 81.24)

84.21 (75.46, 90.31)

16.67 (5.01, 40.05)

96.39 (89.47, 99.20)

0.671 (0.570–0.761)

CRL + HR

83.17 (74.59, 89.31)

50.00 (18.76, 81.24)

87.37 (79.06, 92.77)

20.00 (6.28, 45.95)

96.51(89.82, 99.23)

0.687 (0.587–0.775)

  1. VGG19: a model of the convolutional neural network
  2. Auc Area Under Curve, CI Confidence Interval, CNN convolutional neural networks, CRL crown-rump length, HR heart rate, PPV positive predictive value, NPV negative predictive value