"ECG-CBA: An End-to-End Deep Learning Model for ECG Anomaly Detection Using ..."

Khalid Ammar et al. (2025)

> Home

Details and statistics

DOI: 10.3390/A18110674

access: open

type: Journal Article

metadata version: 2026-01-02

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/algorithms/AmmarFAS25
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/algorithms/AmmarFAS25
Khalid Ammar, Salam Fraihat, Ghazi Al-Naymat, Yousef K. Sanjalawe:
ECG-CBA: An End-to-End Deep Learning Model for ECG Anomaly Detection Using CNN, Bi-LSTM, and Attention Mechanism. Algorithms 18(11): 674 (2025)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.