Exploring interpretability in deep learning prediction of successful ablation therapy for atrial fi brillation

HIGHLIGHTS

  • who: . and colleagues from the Karlsruhe Institute of Technology (KIT), Germany Queen Mary University of London have published the research work: Exploring interpretability in deep learning prediction of successful ablation therapy for atrial fi brillation, in the Journal: (JOURNAL)
  • what: The authors present a novel qualitative and quantitative comparison of established DL interpretability methods for medical imaging and image-based cardiac modelling of RFCA, as well as new quantitative metrics to assess interpretability of FA maps for the image-based cardiac models. The authors propose a DL approach to 1) accurately predict the outcomes of . . .

     

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