Human-like few-shot and one-shot learning of the electrocardiograms: an empirical study investigating the use of a pseudo-coloring technique to improve and explain machine vision predictions of long QT syndrome

Documents similaires

• Human-like visual computing advances explainability and few-shot learning in deep neural networks for complex physiological data
  par: Alahmadi, Alaa, et autres
  Publié: (2025)
• When predict can also explain: few-shot prediction to select better neural latents
  par: Dabholkar, Kabir, et autres
  Publié: (2024)
• An open‐source general purpose machine learning framework for individual animal re‐identification using few‐shot learning
  par: Oscar Wahltinez, et autres
  Publié: (2024)
• Fetal electrocardiogram prediction using machine learning: a random forest-based approach
  par: Moutaib, Mohammed, et autres
  Publié: (2024)
• Dynamical cross-correlations between RR and QT intervals in long-term electrocardiogram recordings
  par: Kokkonen, Jimi, et autres
  Publié: (2024)