Whale optimization algorithm for Covid-19 detection based on ECG

Imene Latreche, Mohamed Akram Khelili, Sihem Slatnia, Okba Kazar, Saad Harous

Research output: Chapter in Book/Report/Conference proceedingChapter


COVID-19 has been declared a global catastrophe in recent years, resulting in several fatalities. The bulk of COVID-19 detection investigations use on X-ray pictures and CT scans of the lungs. Recent clinical research, however, indicated that COVID-19 had an effect on the cardiac signal. As a result, we used the Whale Optimization Algorithm to explore the ECG signal for COVID-19 identification. The model was configured using the WOA used for hyperparameter auto-selection. We used both binary and three-class classification algorithms in the suggested methodology. The created model obtained 99% accuracy for binary classification and 83% accuracy for three-class classification.

Original languageEnglish
Title of host publicationHandbook of Whale Optimization Algorithm
Subtitle of host publicationVariants, Hybrids, Improvements, and Applications
Number of pages13
ISBN (Electronic)9780323953658
ISBN (Print)9780323953641
Publication statusPublished - Jan 1 2023


  • Covid-19 detection
  • Deep learning
  • ECG images
  • Metaheuristic
  • Whale optimization algorithm

ASJC Scopus subject areas

  • General Computer Science


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