Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset

Abstract

Data source variability is a potential contributor to bias in distributed research networks. We call for systematic assessment and reporting of data source variability and data quality in COVID-19 data sharing, as key information for reliable and generalizable machine learning.