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. Author manuscript; available in PMC: 2023 Mar 1.
Published in final edited form as: Resuscitation. 2022 Jan 15;172:17–23. doi: 10.1016/j.resuscitation.2022.01.004

Table 3:

Performance of clinical, imaging and combined models predicting initial EEG state among comatose survivors of cardiac arrest.

Predicted outcome(s)
Model/Inputs Benign vs. suppressed Benign vs. highly pathological Suppressed vs. highly pathological Benign vs. suppressed vs. highly pathological
Clinical covariates
 LR 0.73 (0.02) 0.80 (0.04) 0.74 (0.08) 0.74 (0.04)
 SVM 0.69 (0.04) 0.70 (0.05) 0.63 (0.03) 0.66 (0.03)
 NN 0.73 (0.02) 0.80 (0.05) 0.75 (0.04) 0.75 (0.04)
Imaging
 VGG16 0.69 (0.04) 0.51 (0.03) 0.66 (0.05) 0.60 (0.04)
 ResNet50 0.64 (0.04) 0.55 (0.06) 0.62 (0.02) 0.61 (0.02)
 GoogLeNet 0.66 (0.04) 0.51 (0.07) 0.62 (0.04) 0.58 (0.04)
Combined model NN + VGG16 NN + ResNet50 NN + VGG16 NN + ResNet50
 Performance 0.73 (0.05) 0.61 (0.05) 0.67 (0.06) 0.66 (0.03)

Data are presented as area under the curve with standard deviations.