Acute Respiratory Distress Identification via Multi-Modality Using Deep Learning

Keyphrases

• Acute Respiratory Distress Syndrome 100%
• Clinical Setting 25%
• Color Information 75%
• Confidence Score 25%
• Continuous Monitoring 25%
• Deep Convolutional Neural Network (deep CNN) 25%
• Deep Learning 100%
• Depth Data 25%
• Detection Accuracy 25%
• Detection Probability 25%
• Distress Detection 25%
• Distress Identification 100%
• Early Detection 25%
• Feature Fusion 25%
• Fusion Scheme 25%
• Health Complications 25%
• Human Error 25%
• Late Fusion Technique 25%
• Lighting Conditions 25%
• Medical Devices 25%
• Multimodal Data 75%
• Multimodality 100%
• Pediatric Intensive Care Unit 25%
• Promising Solution 25%
• Respiratory Illness 25%
• Respiratory Parameters 25%
• Severity Levels 25%
• Skin Tone 25%
• Visual Inspection 25%

Computer Science

• Clinical Setting 25%
• Color Information 50%
• Confidence Score 25%
• Continuous Monitoring 25%
• Deep Convolutional Neural Networks 25%
• Deep Learning Method 100%
• Detection Accuracy 25%
• Early Detection 25%
• Experimental Result 25%
• Feature Fusion 25%
• Fusion Technique 25%
• Lighting Condition 25%
• Medical Equipment 25%
• Multimodality 100%

Medicine and Dentistry

• Convolutional Neural Network 25%
• Deterioration 25%
• Feature Fusion 25%
• Human Error 25%
• Intensive Care 25%
• Intensive Care Unit 25%
• Medical Instrument 25%
• Respiratory Disease 25%
• Respiratory Distress 100%
• Visual Examination 25%