On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG.

Journal: IEEE transactions on bio-medical engineering
Published Date:

Abstract

OBJECTIVE: Over the past few years, deep learning (DL) has been used extensively in research for 12-lead electrocardiogram (ECG) analysis. However, it is unclear whether the explicit or implicit claims made on DL superiority to the more classical feature engineering (FE) approaches, based on domain knowledge, hold. In addition, it remains unclear whether combining DL with FE may improve performance over a single modality.

Authors

  • Eran Zvuloni
  • Jesse Read
  • Antônio H Ribeiro
    Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. antonio-ribeiro@ufmg.br.
  • Antonio Luiz P Ribeiro
    Hospital das Clínicas and Faculdade de Medicina, Universidade Federal de Minas Gerais, Av. Prof. Alfredo Balena, 190 - sala 533/Universidade Federal de Minas Gerais (UFMG), Belo Horizonte - MG, Brazil. Electronic address: tom@hc.ufmg.br.
  • Joachim A Behar
    Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel.