The paper focuses on the detection of heart disease through ECG images using advanced technologies, specifically vision transformer models. These models include Google-Vit, Microsoft-Beit, and Swin-Tiny. The study emphasizes the importance of early and accurate detection of heart disease for effective intervention and treatment. The researchers compare the performance of vision transformer models with other studies and conclude that the proposed framework exhibits significant classification results. The integration of sophisticated technologies and computational approaches, like machine learning algorithms, data mining techniques, and predictive modeling frameworks, have improved diagnostic accuracy and risk stratification in heart disease detection.
Publication date: 20 Oct 2023
Project Page: Not provided
Paper: https://arxiv.org/pdf/2310.12630
