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. Author manuscript; available in PMC: 2022 Feb 1.
Published in final edited form as: Future Gener Comput Syst. 2020 Sep 30;115:610–618. doi: 10.1016/j.future.2020.09.040

Table 1:

Comparative results of proposed C-RNN and other architectures for LV status classification.

Model OR Data ACC SEN SPE AUC DR
MLP 0 Val 63.99% 11.00% 92.56% 0.5988 0.4856
Test 50.80% 6.72% 92.62% 0.4934 0.2610

10% Val 63.17% 20.40% 86.22% 0.6258 0.6986
Test 51.81% 10.91% 90.63% 0.5331 0.2958

20% Val 63.77% 22.59% 85.70% 0.6272 0.7162
Test 52.98% 15.84% 88.22% 0.5448 0.3829

30% Val 63.76% 24.90% 84.62% 0.6306 0.7574
Test 52.03% 16.59% 85.67% 0.5397 0.4229

40% Val 63.44% 27.33% 82.87% 0.6361 0.7961
Test 51.53% 17.34% 83.97% 0.5267 0.4667

50% Val 62.96% 30.37% 80.50% 0.6338 0.8734
Test 53.28% 20.63% 84.26% 0.5331 0.4747

CNN+ MLP 0 Val 64.98% 8.92% 94.92% 0.6069 0.4764
Test 51.02% 4.33% 95.32% 0.5361 0.2897

10% Val 64.62% 9.30% 94.52% 0.6056 0.5341
Test 51.38% 5.14% 95.32% 0.5376 0.3253

20% Val 64.20% 14.41% 90.68% 0.6245 0.6236
Test 51.75% 12.11% 89.36% 0.5649 0.4507

30% Val 64.70% 19.06% 89.22% 0.6367 0.6504
Test 53.57% 37.82% 68.51% 0.5699 0.8127

40% Val 64.80% 24.52% 86.54% 0.6487 0.7335
Test 55.17% 57.10% 53.33% 0.5803 1.1318

50% Val 64.82% 25.68% 85.98% 0.6515 0.7723
Test 55.39% 67.41% 43.97% 0.5879 1.3324

RNN+ MLP 0 Val 72.93% 59.35% 80.84% 0.7946 1.300
Test 65.50% 47.68% 82.41% 0.7761 0.7572

10% Val 73.23% 59.91% 80.52% 0.8024 1.2599
Test 62.81% 49.17% 75.74% 0.7360 1.0474

20% Val 72.98% 57.73% 81.50% 0.8022 1.2755
Test 65.42% 58.59% 71.91% 0.7190 1.0073

30% Val 73.77% 59.12% 82.24% 0.7962 1.2681
Test 62.81% 45.14% 79.57% 0.6839 0.9331

40% Val 72.74% 56.87% 81.24% 0.7872 1.2601
Test 62.74% 55.75% 69.36% 0.7172 1.1059

50% Val 72.54% 56.80% 81.10% 0.7869 1.2621
Test 65.07% 48.13% 81.13% 0.6947 1.1040

Proposed C-RNN 0 Val 78.39% 72.02% 81.82% 0.8622 1.291
Test 75.32% 68.01% 82.27% 0.8587 0.9636

10% Val 78.94% 72.39% 82.69% 0.8680 1.2693
Test 74.89% 65.62% 83.69% 0.8613 0.9314

20% Val 78.62% 72.46% 81.98% 0.8597 1.2672
Test 75.96% 71.00% 78.72% 0.8363 1.0201

30% Val 78.45% 71.50% 82.41% 0.8642 1.2551
Test 75.40% 70.55% 80.00% 0.8540 1.0055

40% Val 78.56% 70.99% 82.67% 0.8617 1.2470
Test 76.35% 70.70% 81.70% 0.8568 0.9766

50% Val 78.39% 71.29% 82.28% 0.8597 1.2472
Test 77.07% 75.93% 78.16% 0.8678 1.0617

In the first row, the meanings of all the acronyms and abbreviations are explained as follows: OR: Overlapping Rate; Data: the model was either applied on validation sets or the testing set; ACC: Accuracy; SEN: sensitivity; SPE: specificity; AUC: Area under the ROC curve; DR: Duration ratio.