Correction to “Mitral regurgitation detection and central/eccentric classification using transformer‐based deep learning in multi‐view echocardiography”

Puntos clave

• The primary aim is to correct previously reported outcomes in mitral regurgitation detection using deep learning methods.
• Utilized transformer-based deep learning models for image analysis.
• Analyzed multi-view echocardiography images for improved classification accuracy.
• Implementing corrections based on the latest algorithmic refinements.
• Increased detection accuracy for mitral regurgitation was observed post-correction.
• Classification metrics improved significantly, enhancing diagnostic reliability.
• Specific performance metrics and statistical significance of corrections were detailed.