使用患者报告的结果预测中年和老年人群中的类风湿性关节炎:来自SHARE队列的见解
Fanji Qiu1, Rongrong Zhang2, Friedemann Schwenkreis3
1Movement Biomechanics, Institute of Sport Sciences, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany.
International journal of medical informatics
|April 10, 2025
概括
机器学习模型在识别50岁以上患者的风湿性关节炎 (RA) 中表现出相当的表现. 日常生活中的困难是危险因素,而生活方式活动可能是保护性的,这表明它们在RA评估中的重要性.
科学领域:
- 老年学是指老年学的学科.
- 类风湿病学 类风湿病学
- 人工智能的人工智能
背景情况:
- 全球人口老龄化增加了类风湿性关节炎 (RA) 的患病率.
- 早期识别RA对于及时治疗和降低成本至关重要.
- 机器学习 (ML) 提供了早期RA检测的潜力.
研究的目的:
- 在50岁以上的人群中确定与RA相关的变量.
- 评估ML模型在识别RA患者中的有效性.
主要方法:
- 开发了ML预测模型,包括轻GBM,后勤回归,k-最近邻居,天真贝叶斯,随机森林和XGBoost.
- 利用来自SHARE数据库的患者报告结果 (第7波和第9波).
主要成果:
- 在日常活动中遇到困难 (例如,腰,拉) 被确定为RA风险因素.
- 参与生活方式活动显示了与RA的负面关联.
- 轻GBM模型实现了最高的曲线下面积 (AUC) 0.748.8.
- 后勤回归和轻GBM模型显示了0.902.90的最高准确度.
结论:
- 使用患者报告结果的ML模型显示了合理的性能,但对早期RA识别的潜力有限.
- 日常生活和生活方式活动中的困难是与RA风险相关的重要因素.
- 这些因素应在RA评估的患者病史中考虑.
相关概念视频
Genome-wide Association Studies-GWAS
12.2K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
12.2K
The JAK-STAT Signaling Pathway
8.5K
Several cytokine receptors have tightly bound Janus kinase or JAK proteins attached at their cytosolic tail. Small signaling molecules such as cytokines, growth hormones, or prolactins bind to the cytokine receptors and initiate their dimerization. The dimerization brings the cytosolic JAKs together that trans-phosphorylate and activates each other. The activated JAKs now phosphorylate cytosolic tails of the cytokine receptors, which serve as binding sites for adaptor proteins such as SH2...
8.5K


