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 .…