ArticleThe Journal of international medical research2021
Decision tree analysis for evaluating disease activity in patients with rheumatoid arthritis.
Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Validity and applicability of machine learning models for systemic lupus erythematosus diagnosis.Lupus science & medicine · 2026Article
- Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases.Clinical and experimental medicine · 2026Review
- Identification and validation of an explainable machine learning model for early postoperative pulmonary complications after esophagectomy in patients with esophageal cancer.Journal of gastrointestinal oncology · 2026Article
- Predicting survival in patients with SARS-CoV-2 based on cytokines and soluble immune checkpoint regulators.Frontiers in cellular and infection microbiology · 2024Article
- Machine learning-based models for the prediction of breast cancer recurrence risk.BMC medical informatics and decision making · 2023Article
- Systemic lupus erythematosus with high disease activity identification based on machine learning.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2023Article
- Clinical study of classification and regression tree assisted endometrial biopsy in the diagnosis of endometrial carcinoma.American journal of cancer research · 2023Article
- Beyond Health Services: The Persistent Impact of Early Substance Abuse on Oral Health-related Quality of Life.Journal of International Society of Preventive & Community DentistryArticle
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Authors and funding
5 authors.
Funding
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Abstract
objectiveRheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease characterized by inflammatory synovitis. We developed a new disease activity evaluation system using important cytokines to help doctors better evaluate disease activity in patients with RA.
methodsFlow cytometry was used to detect the levels of seven cytokines. Then, the results were analyzed using an R language decision tree.
resultsThe levels of six cytokines, namely interleukin (IL)-2, IL-4, IL-6, IL-10, tumor necrosis factor-α, and interferon-γ, were significantly different between the active disease and remission stages. Decision tree analysis of the six cytokines with statistical significance identified two judgment rules for the remission stage and three judgment rules for the active disease stage.
conclusionWe proposed the use of the decision tree method to analyze cytokine levels in patients with RA and obtain a more intuitive and objective RA disease activity scoring system. This method revealed the relationships of IL-6 and TNF-α levels with inflammatory characteristics in patients with RA, which can help predict disease activity.
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