A few weeks ago, I shipped PneumoScan AI a deep learning model that analyzes chest X-ray images and detects pneumonia in seconds, with 90%+ accuracy. It's live, it's free, and anyone can use it right now. 🔗 pneumonia-scan-ai.netlify.app This is the story of how I built it — and everything I learned along the way. Why Pneumonia? Pneumonia kills over 2 million people annually. A huge portion of those deaths happen in low-resource areas where radiologists are scarce and diagnosis is slow. I'm not claiming to solve that problem. But I wanted to build something that mattered not just another MNIST classifier or iris flower predictor. Medical imaging felt real. The Dataset I used the Chest X-Ray Images (Pneumonia) dataset from Kaggle. 5,800+ clinical chest X-ray images Two classes: NORMAL and PNEUMONIA (Viral & Bacterial) Real hospital data from Guangzhou Women and Children's Medical Center One thing I learned immediately: the dataset is imbalanced .…