Diagnosis of Takotsubo Syndrome by Robust Feature Selection from the Complex Latent Space of DL-Based Segmentation Network

Keyphrases

• Takotsubo Syndrome 100%
• Segmentation Network 100%
• Deep Learning Segmentation 100%
• Latent Space 100%
• Robust Selection 100%
• Differential Diagnosis 50%
• ST-elevation Myocardial Infarction (STEMI) 50%
• Segmentation Model 50%
• Feature Selection Methods 50%
• Echocardiogram Videos 50%
• Latent Features 50%
• Clinical Features 25%
• Disease-related 25%
• Diagnostic Accuracy 25%
• Overfitting 25%
• Overall Accuracy 25%
• Long-term Disease 25%
• Disease Prediction 25%
• Medical Imaging Modalities 25%
• Disease Prognosis 25%
• Classification Model 25%
• Deep Learning Model 25%
• Downstream Analysis 25%
• LASSO Algorithm 25%
• Handcrafted Features 25%
• Rare Cardiac Diseases 25%

Computer Science

• Feature Selection 100%
• Network Segmentation 100%
• Deep Learning Method 100%
• Feature Extraction 100%
• Segmentation Model 50%
• Differential Diagnosis 50%
• Medical Imaging 25%
• Classification Models 25%
• Deep Learning Model 25%

Biochemistry, Genetics and Molecular Biology

• Feature Extraction 100%
• ST Elevation 50%