This document discusses MAWI Solutions' ECG processing pipelines and their evolution from using traditional mathematical models to machine learning approaches. It provides an overview of how ECG signals work and are used in medicine. It then outlines the key steps in ECG processing - filtration, annotation, validation, and disease detection. For each step, it compares the traditional approaches using mathematical models to MAWI's newer machine learning-based approaches, providing examples of how deep learning algorithms can be applied to tasks like signal denoising, rhythm classification, and atrial fibrillation detection.