Training Recurrent Neural Network-Based Model to Predict COVID-19 Patient Risk for PASC using Pytorch_EHR – Hands-on Tutorial on N3C

Pytorch_EHR is a codebase enabling fast prototyping of deep learning-based predictive models using electronic health records structured data. Rather than a collection of vertical pipelines implementing methods from papers claiming state-of the-art results, Pytorch_EHR offers efficient implementations of data flow, padding, embeddings, choices of popular recurrent neural networks (RNN) cells and layers structures, prediction heads, and also predictions explanation and visualization. This tutorial will provide participants with a clear understanding of deep learning theoretical concepts behind Pytorch_EHR different components, as well as hands-on experience in building an explainable RNN-based model to solve a real-world clinical problem on a cloud-based platform hosting the National COVID Cohort Collaborative (N3C) data. URL: https://github.com/ZhiGroup/pytorch_ehr