Cited by

CU Ventricular Tachyarrhythmia Database (v1.0.0)

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5 publications cite any version of this project, newest first.

• A Novel Noise-Resilient and Explainable Machine Learning Framework for Accurate and Robust ECG-Based Heart Disease Diagnosis
  Abdullah Alhalabi, Saleh I. Alzahrani, Lamia Al Saikhan et al. medRxiv, 2025.
• ECG analysis of ventricular fibrillation dynamics reflects ischaemic progression subject to variability in patient anatomy and electrode location
  Hector Martinez‐Navarro, Ambre Bertrand, Rubén Doste et al. Frontiers in Cardiovascular Medicine, 2024.
• Graph Attention Networks Based Cardiac Arrest Diagnosis
  Phong Tuc Vu, Anh Nguyen, Minh Tuan Nguyen. International Conference on Advanced Technologies for Communications, 2024.
• A Hybrid GAN-Based DL Approach for the Automatic Detection of Shockable Rhythms in AED for Solving Imbalanced Data Problems
  Kamana Dahal, Mohd. Hasan Ali. Electronics, 2022.
• Overview of Machine Learning and Deep Learning Approaches for Detecting Shockable Rhythms in AED in the Absence or Presence of CPR
  Kamana Dahal, Mohd. Hasan Ali. Electronics, 2022.

Citation data from OpenAlex, updated weekly. Papers that use the project without citing it may be missing.