Identification of Multimorbidity Patterns in Rheumatoid Arthritis Through Machine Learning
Abstract
Recognizing that the interrelationships between chronic conditions that complicate rheumatoid arthritis (RA) are poorly understood, we aimed to identify patterns of multimorbidity and to define their prevalence in RA through machine learning.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 19, 2022
- Source ID
- 10.1002/acr.24956
Entities
People
- Brian C Sauer
- Bryant R England
- Christian Haas
- Fang Yu
- Fenglong Xie
- Harlan Sayles
- Jeffrey R Curtis
- Joshua F Baker
- Kaleb Michaud
- Lotfollah Najjar
- Punyasha Roul
- Ted R Mikuls
- Yangyuna Yang
Organizations
- American College of Rheumatology Research and Education Foundation
- National Institute of Arthritis and Musculoskeletal and Skin Diseases
- National Institute of General Medical Sciences
- National Institute on Alcohol Abuse and Alcoholism
- Patient-Centered Outcomes Research Institute
- United States Department of Defense
- United States Department of Veterans Affairs
- University of Alabama at Birmingham
- University of Nebraska Medical Center
- University of Nebraska Omaha
- University of Nebraska–Lincoln
- University of Pennsylvania
- University of Utah