A Hybrid Optimized Framework for the Classification and Detection of Cardiac Diseases

@article{1722160,
      author = {Pothanaboina Lavanya, Chandana Padarthi, Sudagani Chandra Bhavani , Tokala Sravani, Dr. R. Sudha Kishore; Dr. K. Kranthi Kumar},
      title = {A Hybrid Optimized Framework for the Classification and Detection of Cardiac Diseases},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {2},
      pages = {209-217},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1722160.pdf},
      abstract = {The research study ventures into heart signal evaluation and diagnosis machine learning using Vision Transformer (ViT) as the main computation building block. In his work Vazifecas constructs a one- dimensional signal for separating P, QRS, and T segments of heart electrical waves from ECG signals. Staking Ensemble enhances The Cardiovascular ECG Images dataset robustness levels. A Whale- Optimization performs model diagnosis of heart disease in the optimization process of heart signals.},
      keywords = {Cardiovascular Disease, Convolutional Neural Network (CNN), vision transformer (VIT), Multi-Layer Perceptron (MLP), Whole Optimization Algorithm (WOA).},
      month = {August},
      doi = {https://doi.org/10.64388/IREV10I2-1722160}
  }