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Models/5th year medical student

5th year medical student

Reported on 30 benchmarks across 5 tasks · 1 paper

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

Medical18 results

  • ECG ClassificationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (1dAVb)· 2019-04-02
    0.732
    best: 0.893 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • ECG ClassificationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (AF)· 2019-04-02
    0.706
    best: 0.857 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • ECG ClassificationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (LBBB)· 2019-04-02
    0.915
    best: 0.984 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • ECG ClassificationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (RBBB)· 2019-04-02
    0.928
    best: 0.932 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • ECG ClassificationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (SB)· 2019-04-02
    0.75
    best: 0.882 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • ECG ClassificationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (ST)· 2019-04-02
    0.857
    best: 0.933 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Photoplethysmography (PPG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (1dAVb)· 2019-04-02
    0.732
    best: 0.893 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Photoplethysmography (PPG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (AF)· 2019-04-02
    0.706
    best: 0.857 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Photoplethysmography (PPG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (LBBB)· 2019-04-02
    0.915
    best: 0.984 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Photoplethysmography (PPG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (RBBB)· 2019-04-02
    0.928
    best: 0.932 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Photoplethysmography (PPG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (SB)· 2019-04-02
    0.75
    best: 0.882 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Photoplethysmography (PPG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (ST)· 2019-04-02
    0.857
    best: 0.933 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Blood pressure estimationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (1dAVb)· 2019-04-02
    0.732
    best: 0.893 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Blood pressure estimationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (AF)· 2019-04-02
    0.706
    best: 0.857 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Blood pressure estimationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (LBBB)· 2019-04-02
    0.915
    best: 0.984 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Blood pressure estimationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (RBBB)· 2019-04-02
    0.928
    best: 0.932 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Blood pressure estimationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (SB)· 2019-04-02
    0.75
    best: 0.882 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Blood pressure estimationonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (ST)· 2019-04-02
    0.857
    best: 0.933 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949

Methodology12 results

  • Electrocardiography (ECG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (1dAVb)· 2019-04-02
    0.732
    best: 0.893 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Electrocardiography (ECG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (AF)· 2019-04-02
    0.706
    best: 0.857 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Electrocardiography (ECG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (LBBB)· 2019-04-02
    0.915
    best: 0.984 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Electrocardiography (ECG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (RBBB)· 2019-04-02
    0.928
    best: 0.932 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Electrocardiography (ECG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (SB)· 2019-04-02
    0.75
    best: 0.882 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Electrocardiography (ECG)onElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (ST)· 2019-04-02
    0.857
    best: 0.933 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Medical waveform analysisonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (1dAVb)· 2019-04-02
    0.732
    best: 0.893 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Medical waveform analysisonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (AF)· 2019-04-02
    0.706
    best: 0.857 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Medical waveform analysisonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (LBBB)· 2019-04-02
    0.915
    best: 0.984 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Medical waveform analysisonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (RBBB)· 2019-04-02
    0.928
    best: 0.932 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Medical waveform analysisonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (SB)· 2019-04-02
    0.75
    best: 0.882 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949
  • Medical waveform analysisonElectrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)
    F1 (ST)· 2019-04-02
    0.857
    best: 0.933 (DNN)
    Automatic diagnosis of the 12-lead ECG using a deep neural networkarXiv:1904.01949