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Models/XSleepNet (C4-A1 only)

XSleepNet (C4-A1 only)

Reported on 8 benchmarks across 2 tasks · 1 paper · 8 SOTA

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

Medical8 results

  • Sleep QualityonSHHS (single-channel)
    Cohen's Kappa· 2020-07-08
    0.828
    best: 0.841 (MC2SleepNet 50% Masking (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492
  • Sleep QualityonSHHS (single-channel)
    Macro-F1· 2020-07-08
    0.801
    best: 0.823 (MC2SleepNet 15% Masking (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492
  • Sleep QualityonMASS (single-channel)
    Cohen's Kappa· 2020-07-08
    0.788
    best: 0.811 (SleePyCo (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492
  • Sleep QualityonMASS (single-channel)
    Macro-F1· 2020-07-08
    0.806
    best: 0.825 (SleePyCo (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492
  • Sleep Stage DetectiononSHHS (single-channel)
    Cohen's Kappa· 2020-07-08
    0.828
    best: 0.841 (MC2SleepNet 50% Masking (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492
  • Sleep Stage DetectiononSHHS (single-channel)
    Macro-F1· 2020-07-08
    0.801
    best: 0.823 (MC2SleepNet 15% Masking (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492
  • Sleep Stage DetectiononMASS (single-channel)
    Cohen's Kappa· 2020-07-08
    0.788
    best: 0.811 (SleePyCo (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492
  • Sleep Stage DetectiononMASS (single-channel)
    Macro-F1· 2020-07-08
    0.806
    best: 0.825 (SleePyCo (C4-A1 only))
    SOTA
    XSleepNet: Multi-View Sequential Model for Automatic Sleep StagingarXiv:2007.05492