Subtyping of common complex diseases and disorders by integrating heterogeneous data. Identifying clusters among women with lower urinary tract symptoms in the LURN study

Authors

Victor P. Andreev, Arbor Research Collaborative for Health
H Henry Lai, Washington University School of Medicine in St. Louis
et al

Journal

PLoS One

Publication Date

1-1-2022

Volume

17

Issue

6

First Page

e0268547

Document Type

Open Access Publication

DOI

10.1371/journal.pone.0268547

Rights and Permissions

Andreev VP, Helmuth ME, Liu G, Smith AR, Merion RM, et al. (2022) Subtyping of common complex diseases and disorders by integrating heterogeneous data. Identifying clusters among women with lower urinary tract symptoms in the LURN study. PLOS ONE 17(6): e0268547. https://doi.org/10.1371/journal.pone.0268547. © 2022 Andreev et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Recommended Citation

Andreev, Victor P.; Lai, H Henry; and et al, "Subtyping of common complex diseases and disorders by integrating heterogeneous data. Identifying clusters among women with lower urinary tract symptoms in the LURN study." PLoS One. 17, 6. e0268547 (2022).
https://digitalcommons.wustl.edu/oa_4/120