Cluster analysis identifies unmet healthcare needs among patients with rheumatoid arthritis-Reference-Cited by-同舟云学术

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Cluster analysis identifies unmet healthcare needs among patients with rheumatoid arthritis

Published:2021-09-13 Issue: Volume: Page:1-8
ISSN:0300-9742
Container-title:Scandinavian Journal of Rheumatology
language:en
Short-container-title:Scandinavian Journal of Rheumatology

Author:

Mars N¹²,Kerola AM¹³,Kauppi MJ³⁴,Pirinen M²⁵⁶,Elonheimo O¹,Sokka-Isler T⁷

Affiliation:

1. Faculty of Medicine, University of Helsinki, Helsinki, Finland

2. Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland

3. Department of Internal Medicine, Päijät-Häme Joint Authority for Health and Wellbeing, Lahti, Finland

4. Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland

5. Department of Public Health, University of Helsinki, Helsinki, Finland

6. Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland

7. Department of Rheumatology, Jyväskylä Central Hospital, Jyväskylä, Finland

Funder

Academy of Finland

Foundation for Research in Rheumatology

Finnish Research Foundation for Rheumatic Diseases

Publisher

Informa UK Limited

Subject

Immunology,General Medicine,Immunology and Allergy,Rheumatology

Link

https://www.tandfonline.com/doi/pdf/10.1080/03009742.2021.1944306

Reference26 articles.

1. Effects of Achieving Target Measures in Rheumatoid Arthritis on Functional Status, Quality of Life, and Resource Utilization: Analysis of Clinical Practice Data

2. The clinical status and economic savings associated with remission among patients with rheumatoid arthritis: leveraging linked registry and claims data for synergistic insights

3. Call for action: how to improve use of patient-reported outcomes to guide clinical decision making in rheumatoid arthritis

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Determination of the factors associated with antigen-specific CD4+ T-cell responses to BNT162b2 in patients with rheumatoid arthritis;RMD Open;2024-01

2. Unsupervised cluster analysis of clinical and ultrasound features reveals unique gout subtypes: Results from the Egyptian College of Rheumatology (ECR);Diabetes & Metabolic Syndrome: Clinical Research & Reviews;2023-12

3. Patients with rheumatoid arthritis presenting with mono- or oligo-arthritis and high VAS-ratings remain the most fatigued during 5 years of follow-up;Rheumatology;2023-08-26

4. Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs;PLOS Computational Biology;2023-06-02

5. Using Unsupervised Machine Learning Methods to Cluster Comorbidities in a Population‐Based Cohort of Patients With Rheumatoid Arthritis;Arthritis Care & Research;2022-09-15

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