Deep significance clustering: A novel approach for identifying risk-stratified and predictive patient subgroups

Huang, Y., Liu, Y., Steel, P. A. D., Axsom, K. M., Lee, J. R., Tummalapalli, S. L., Wang, F., Pathak, J., Subramanian, L., & Zhang, Y. (2021). Deep significance clustering: a novel approach for identifying risk-stratified and predictive patient subgroups. Journal of the American Medical Informatics Association, 28(12), 2641–2653. https://doi.org/10.1093/jamia/ocab203
Authors:
Yufang Huang
Yifan Liu
Peter A. D Steel
Kelly M Axsom
John R Lee
Sri Lekha Tummalapalli
Fei Wang
Jyotishman Pathak
Lakshminarayanan Subramanian
Yiye Zhang
Affiliated Authors:
Kelly M Axsom
Author Keywords:
machine learning
predictive clustering
risk stratification
Publication Type:
Article
Unique ID:
10.1093/jamia/ocab203
PMID:
Publication Date:
Data Source:
Scopus

Record Created: