This work was aimed at investigating image feature recognition and clinical nursing of children’s rheumatoid arthritis- (CRA-) related lung injury under maximum correlation minimum redundancy algorithm of machine learning. In this study, 18 children with CRA in the hospital were selected as the rheumatoid group to explore the nursing method, and 18 healthy children were selected as the control group. The maximum correlation minimum redundancy algorithm of machine learning was compared with the information gain algorithm and the Fisher score algorithm and applied in computed tomography (CT) images of 18 CRA children. The classification accuracy of the algorithm in this study (94.52%) was higher than that of the information gain algorithm (88.64%) and Fisher score algorithm (81.24%). CT alveolitis score (2.35 ± 0.72 points) of children from the rheumatoid group was markedly higher than that of the control group (1.21 ± 0.24 points) (t = 2.147 and ). The nitric oxide level (14.00 ppb) of children from the rheumatoid group increased greatly compared with the control group (10.00 ppb) (). CRA can cause a decline of lung function in children, while the nitric oxide level exhaled by children can assess the activity of RA. In addition, adopting active nursing methods can help children get better.

中文翻译：

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基于机器学习的儿童类风湿性关节炎相关肺损伤的图像特征识别及临床护理

本工作旨在研究机器学习最大相关最小冗余算法下儿童类风湿性关节炎（CRA-）相关肺损伤的图像特征识别和临床护理。本次研究选取住院CRA患儿18例作为类风湿组探索护理方法,选取18例健康儿童作为对照组。将机器学习的最大相关最小冗余算法与信息增益算法和Fisher评分算法进行比较，并应用于18名CRA儿童的计算机断层扫描（CT）图像。本研究算法的分类准确率（94.52%）高于信息增益算法（88.64%）和Fisher score算法（81.24%）。CT 肺泡炎评分 (2.35 ± 0.t  = 2.147 和）。与对照组（10.00 ppb）相比，类风湿组儿童的一氧化氮水平（14.00 ppb）显着增加（）。CRA会导致儿童肺功能下降，而儿童呼出的一氧化氮水平可以评估RA的活动性。此外，采用积极的护理方法可以帮助孩子变得更好。