Limestone: High-throughput candidate phenotype generation via tensor factorization
A nonnegative tensor factorization model that achieves high-throughput phenotyping. The method simultaneously generates multiple phenotypes with no human intervention. Our algorithm generally generates concise and clinically meaningful phenotypes. The model improves heart failure prediction performance on a cohort of 31K patients.
nonnegative tensor factorization dimensionality reduction ehr phenotyping