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Models/AIOSA CNN+LSTM

AIOSA CNN+LSTM

Reported on 9 benchmarks across 1 task · 1 paper · 9 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical9 results

Sleep QualityonApnea-ECG
AUC Per-segment· 2023-02-10
0.981
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
Accuracy Per-patient· 2023-02-10
1
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
Accuracy Per-segment· 2023-02-10
0.936
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
F1 Per-patient· 2023-02-10
1
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
F1 Per-segment· 2023-02-10
0.916
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
Sensitivity Per-patient· 2023-02-10
1
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
Sensitivity Per-segment· 2023-02-10
0.912
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
Specificity Per-patient· 2023-02-10
1
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179
Sleep QualityonApnea-ECG
Specificity Per-segment· 2023-02-10
0.951
SOTA
AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning arXiv:2302.05179