ConCAD: Contrastive Learning-Based Cross Attention for Sleep Apnea Detection

Keyphrases

• Learning-based 100%
• Contrastive Learning 100%
• Sleep Apnea Detection 100%
• Expert Knowledge 40%
• Clinical Application 20%
• Sleep Apnea 20%
• Clinically Significant 20%
• Recent Advancements 20%
• Detection Performance 20%
• Weight-based 20%
• Knowledge Learning 20%
• Data Characteristics 20%
• Fusion Strategy 20%
• Deep Learning Model 20%
• Deep Learning Methods 20%
• Explicit Aspects 20%
• Benchmarking Method 20%
• Model Generalization 20%
• Attention Weight 20%
• Embedding Space 20%

Computer Science

• Contrastive Learning 100%
• Expert Knowledge 40%
• Deep Feature 40%
• Annotation 20%
• Clinical Application 20%
• Detection Performance 20%
• Data Characteristic 20%
• Attention (Machine Learning) 20%
• Deep Learning Model 20%
• Embedding Space 20%

Neuroscience

• Obstructive Sleep Apnea 100%