Pneumonia Detection App Technical Report

Pneumonia remains one of the leading causes of respiratory illness worldwide. This work presents an automated pneumonia detection and severity classification system based on deep learning techniques. A MobileNetV2 convolutional neural network pretrained on ImageNet is employed for feature extraction and binary classification of chest X-ray images into Normal and Pneumonia categories. The model is trained using the Kaggle Chest X-Ray Pneumonia dataset and deployed through a Streamlit-based web application for real-time inference. The system further maps prediction probabilities into severity categories to improve interpretability and assist clinical screening workflows. Experimental evaluation demonstrates effective classification performance while maintaining a lightweight computational footprint suitable for deployment on standard hardware.