Identifying Bladder Phenotypes After Spinal Cord Injury With Unsupervised Machine Learning: A New Way to Examine Urinary Symptoms and Quality of Life-Reference-Cited by-同舟云学术

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Identifying Bladder Phenotypes After Spinal Cord Injury With Unsupervised Machine Learning: A New Way to Examine Urinary Symptoms and Quality of Life

Published:2024-07 Issue:1 Volume:212 Page:114-123
ISSN:0022-5347
Container-title:Journal of Urology
language:en
Short-container-title:Journal of Urology

Author:

Welk Blayne¹²,Zhong Tianyue²,Myers Jeremy³,Stoffel John⁴,Elliot Sean⁵,Lenherr Sara M.³,Lizotte Daniel²⁶

Affiliation:

1. Department of Surgery, Western University, London, Ontario, Canada

2. Department of Epidemiology and Biostatistics, Western University, London, Ontario, Canada

3. Department of Surgery (Urology), University of Utah, Salt Lake City, Utah

4. Department of Urology, University of Michigan, Ann Arbor, Michigan

5. Department of Urology, University of Minnesota, Minneapolis, Minnesota

6. Department of Computer Science, Western University, London, Ontario, Canada

Publisher

Ovid Technologies (Wolters Kluwer Health)

Link

http://www.auajournals.org/doi/pdf/10.1097/JU.0000000000003984

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1. Editorial Comment;Journal of Urology;2024-07

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