Demo - N3C Machine Learning PASC/Long COVID Phenotype Algorithm in the All of Us dataset

This demonstration workspace is a collaboration between the All of Us Research Program, National COVID Cohort Collaborative (N3C), PCORnet, and NIH/RECOVER to examine and identify participant risk of Long COVID utilizing the N3C's machine learning (ML) PASC/Long COVID Phenotype algorithm within the All of Us Researcher Workbench. The XGBoost machine learning model was used to identify potential patients with PASC/Long COVID, which was initially published by Emily et al. These models were subsequently implemented within the All of Us Controlled Tier dataset (C2022Q2R2; v6). 

 

This featured workspace and associated notebook provides a step-by-step guide for the implementation of N3C's ML Model for identification of PASC/Long COVID Phenotype in the All of Us dataset. 

 

Was this article helpful?

0 out of 0 found this helpful

Have more questions? Submit a request