Data Access, Data Bias, Data Equity

When deploying machine learning algorithms in healthcare, a clear plan for assessing the underlying data used for training the algorithm is critical for auditing performance and troubleshooting when errors occur. Algorithmic stewardship is a useful framework for managing the issues of data access, bias, and equity.