Integrating hypertension phenotype and genotype with hybrid non-negative matrix factorization
Abstract
Hypertension is a heterogeneous syndrome in need of improved subtyping using phenotypic and genetic measurements with the goal of identifying subtypes of patients who share similar pathophysiologic mechanisms and may respond more uniformly to targeted treatments. Existing machine learning approaches often face challenges in integrating phenotype and genotype information and presenting to clinicians an interpretable model. We aim to provide informed patient stratification based on phenotype and genotype features.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 15, 2018
- Source ID
- 10.1093/bioinformatics/bty804
Entities
People
- Chengsheng Mao
- Donna Arnett
- Faraz S Ahmad
- Fei Wang
- Marguerite R. Irvin
- Sanjiv J. Shah
- Yiben Yang
- Yuan Luo
Organizations
- American Heart Association
- Cornell University
- National Institutes of Health
- National Science Foundation
- Northwestern University
- Office of Naval Research
- University of Alabama at Birmingham
- University of Kentucky