Abstract
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 P < 0.05 ). The nitric oxide level (14.00 ppb) of children from the rheumatoid group increased greatly compared with the control group (10.00 ppb) ( P < 0.05 ). 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.
Highlights
Children’s rheumatoid arthritis (CRA) is a systemic connective tissue disease, mainly manifested by fever, joint swelling, and pain, often accompanied by rash and the enlargement of liver and spleen lymph nodes. e lungs will be involved because the lungs contain a large number of capillaries and connective tissues, and the serosal membrane, lung parenchyma, and lung airways will be involved, resulting in lung nodules and bronchitis [1]
E maximum correlation minimum redundancy algorithm of machine learning was compared with the information gain algorithm and the Fisher score algorithm and applied to the computed tomography (CT) images of 18 children with CRA. e objective of this study was to explore the CT imaging features and clinical nursing of children’s rheumatoid arthritis- (CRA-)related lung injury
A total of 36 children diagnosed with CRA in our hospital from October 2018 to December 2019 were selected in this study: 18 cases with rheumatoid arthritis as the rheumatoid group and the remaining 18 children as the control group
Summary
Children’s rheumatoid arthritis (CRA) is a systemic connective tissue disease, mainly manifested by fever, joint swelling, and pain, often accompanied by rash and the enlargement of liver and spleen lymph nodes. e lungs will be involved because the lungs contain a large number of capillaries and connective tissues, and the serosal membrane, lung parenchyma, and lung airways will be involved, resulting in lung nodules and bronchitis [1]. Children’s rheumatoid arthritis (CRA) is a systemic connective tissue disease, mainly manifested by fever, joint swelling, and pain, often accompanied by rash and the enlargement of liver and spleen lymph nodes. E lungs will be involved because the lungs contain a large number of capillaries and connective tissues, and the serosal membrane, lung parenchyma, and lung airways will be involved, resulting in lung nodules and bronchitis [1]. Wojcik et al [2] pointed out that the pathogenesis of CRA was that the citrulline in the lungs would be immune under the condition of oxidative stress, which induced successive immune responses in other organs or tissues containing citrulline. Erefore, it is necessary to identify children with CRA promptly and carry out nursing interventions, to prevent the deterioration of lung injury, which is of positive significance for improving the prognosis of children There are still difficulties in the diagnosis of lung injury. erefore, it is necessary to identify children with CRA promptly and carry out nursing interventions, to prevent the deterioration of lung injury, which is of positive significance for improving the prognosis of children
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