Machine-Learning-Enabled Diagnostics with Improved Visualization of Disease Lesions in Chest X-ray Images

Keyphrases

• Chest X-ray Images 100%
• Machine Learning 100%
• Saliency Map 100%
• Improved Visualization 100%
• COVID-19 75%
• Class Activation Map 75%
• Pneumonia 50%
• Region of Interest 50%
• Deep Learning 50%
• Classification Task 50%
• Medical Imaging 25%
• Healthy Individuals 25%
• Infection Severity 25%
• X-ray Film 25%
• Disease Diagnosis 25%
• Neural Network 25%
• Three-class 25%
• Severity Assessment 25%
• Chest X-ray 25%
• Class-specific 25%
• Classification Accuracy 25%
• Image Enhancement 25%
• Medical Practitioners 25%
• Segmentation-based 25%
• Existing Techniques 25%
• Accuracy Measure 25%
• Convolutional Neural Network 25%
• Computational Tomography 25%
• Data Augmentation 25%
• Architecture-centric 25%
• Assessment Index 25%
• Chest X-ray Classification 25%
• Model Training 25%
• Suspicious Region 25%
• Gradient-weighted Class Activation Mapping (Grad-CAM) 25%
• Visual Geometry Group-16 (VGG16) 25%

Computer Science

• Machine Learning 100%
• Learning System 100%
• Feature Map 100%
• COVID-19 75%
• Classification Task 50%
• Medical Imaging 25%
• Neural Network 25%
• Image Enhancement 25%
• Classification Accuracy 25%
• Learning Approach 25%
• Convolutional Neural Network 25%
• Deep Learning Method 25%
• Data Augmentation 25%
• Suspicious Region 25%
• VGG-16 25%
• Deep Learning Technique 25%