AI-Powered Pediatric Pneumonia Detection Achieves Near-Perfect Accuracy

The study demonstrates the significant potential of transfer learning for medical image analysis, achieving impressive accuracy in pediatric pneumonia detection. However, the single-center dataset and lack of external validation limit the generalizability of the findings. Further research should focus on multi-center validation and addressing potential biases in the dataset.

• •Fine-tuned ResNet50 achieved 99.43% accuracy in detecting pediatric pneumonia.
• •Transfer learning outperformed custom CNNs trained from scratch.
• •Grad-CAM visualizations provided explainability for model predictions.