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Table 2 The area under receiver operating characteristic curves of convolutional neural network’s classification on calcified plaques with motion artifacts

From: Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors

Plaque density Inception v3 ResNet101 DenseNet201
High 0.952 (0.939–0.964) 0.972 (0.962–0.980) 0.970 (0.960–0.978)
Medium-1 0.951 (0.939–0.962) 0.955 (0.943–0.965) 0.962 (0.951–0.972)
Medium-2 0.980 (0.970–0.989) 0.974 (0.969–0.981) 0.976 (0.970–0.982)
Low 0.982 (0.976–0.986) 0.981 (0.974–0.992) 0.986 (0.982–0.994)
  1. The data is expressed as area under the curve (95% confidence interval)