Towards building foundation models with millions of ECG

This talk will explore the possibilities of using first of its kind large scale ECG dataset to build foundation models that enable better cardiac care. We will discuss the current trends and challenges in disease detection in ECG and then will explore the use of Self supervised learning to build foundation models. We will provide insights into training methods and benchmark the results across multiple deep learning architectures. The talk will showcase interesting results with the potential to revolutionize cardiac care. This will be a useful session for those working with large scale healthcare datasets.