most citedLearning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records

12 citations · 12 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2020★ 12 cited

Learning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records

Kejing Yin, William K. Cheung, Benjamin C. M. Fung +1

Non-negative tensor factorization has been shown a practical solution to automatically discover phenotypes from the electronic health records (EHR) with minimal human supervision.…