Interpretation of lung disease classification with light attention connected module

Keyphrases

• Lung Disease 100%
• Lung Disease Classification 100%
• Stethoscope 60%
• Respiratory Sounds 40%
• High Performance 20%
• Early Diagnosis 20%
• Classification Model 20%
• Sensitivity Specificity 20%
• Disease-related 20%
• Expert Opinion 20%
• Attention Module 20%
• Lung Sounds 20%
• Balanced Accuracy 20%
• Deep Learning 20%
• F1 Score 20%
• Medical Practitioners 20%
• Obstructive Disease 20%
• Gradient-weighted Class Activation Mapping (Grad-CAM) 20%
• Score Accuracy 20%
• COVID-19 Pandemic 20%
• Log-Mel Spectrogram 20%
• Adventitious Sound 20%
• VGGish 20%
• ECA-Net 20%
• Efficient Channel Attention Module 20%
• Smart Medical 20%
• Attention Effect 20%
• Artificial Intelligence Models 20%
• Open Lung 20%

Medicine and Dentistry

• Nosology 100%
• Silo-Filler's Disease 100%
• Disease 28%
• Respiratory Sounds 28%
• Early Diagnosis 14%
• COVID-19 14%
• Intelligence 14%
• Lung 14%

Agricultural and Biological Sciences

• Lung 100%
• Expert Opinion 12%
• Artificial Intelligence 12%