Medical AI at the Edge: Compressing Neural Networks to 8.9 KB of Pure C

This work demonstrates that sophisticated machine learning can run efficiently on severely resource-constrained devices without cloud infrastructure. By training a neural network on real medical data and compressing it to just 8.9 kB of pure C, the author opens practical pathways for deploying medical AI directly on microcontrollers—enabling privacy-preserving inference and real-time edge computing for healthcare IoT applications.