Automatic diagnosis of the 12-lead ECG using a deep neural network

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in…

• N
  Nvidia
• CD
  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
• CN
  Conselho Nacional de Desenvolvimento Científico e Tecnológico

  Award: 465518/2014-1
• KO
  Knut och Alice Wallenbergs Stiftelse
• FD
  Fundação de Amparo à Pesquisa do Estado de Minas Gerais
• UU
  Uppsala Universitet