Deep Learning Models for Lung Disease Classification from X-rays
A study on arXiv (2607.26580) evaluates VGG16, VGG19, and ResNet50 for classifying lung ailments from X-ray images, including pneumonia, tuberculosis, lung cancer, and normal lungs. All models were trained on a large dataset. ResNet50 achieved the best performance due to its efficiency and accuracy. The research addresses the urgent need for early detection of respiratory diseases using convolutional neural networks.
Key facts
- Study uses VGG16, VGG19, and ResNet50 for lung disease classification
- Diseases classified: pneumonia, tuberculosis, lung cancer, normal lungs
- Models trained on a vast amount of X-ray images
- ResNet50 performed best among the three models
- Research published on arXiv with ID 2607.26580
- Addresses urgent need for early detection of respiratory diseases
- Convolutional neural networks show promise in medical imaging
- Study provides detailed performance analysis of the models
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