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Table 1 (abstract P153). Experimental results (superslow bleeding subjects)

From: 39th International Symposium on Intensive Care and Emergency Medicine

Model AUC AUC@FPR<1% TPR@FPR=0.1% TNR@FNR=1%
Support Vector Machine 0.8936 0.5306 0.0132 ± 0.0012 0.0631 ± 0.0038
Logistic Regression 0.8445 0.5132 0.0062 ± 0.0014 0.0484 ± 0.0083
Naive Recurrent Neural Network (nRNN) 0.9015 0.6077 0.0439 ± 0.2558 0.0583 ± 0.2875
RF on statistical features (baseline) 0.9705 0.6386 0.1456 ± 0.3242 0.6386 ± 0.1972
Long Short-Term Memory (LSTM) 0.9263 0.7010 0.3289 ± 0.1357 0.0981 ± 0.3140
Gated Recurrent Unit (GRU) 0.9449 0.7469 0.3832 ± 0.2267 0.2227 ± 0.2881
Dilated, causal convolution 0.9360 0.5390 0.0163 ± 0.3763 0.1564 ± 0.1991