Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing

To explore the application of self-efficacy in X-ray image analysis based on deep convolutional neural network (DCNN) in the care and treatment of osteoporosis patients with rheumatoid arthritis. In this study, 90 patients with osteoporosis were divided into the control group and the experimental gr...

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Autores principales:	Yaqin Geng, Ting Liu, Yu Ding, Wei Liu, Jiayi Ye, Linlin Hu, Li Ruan
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/9ae4d3600c5d4b0faf3a9589ccfc7ecd
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spelling	oai:doaj.org-article:9ae4d3600c5d4b0faf3a9589ccfc7ecd2021-11-08T02:36:16ZDeep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing1875-919X10.1155/2021/9959617https://doaj.org/article/9ae4d3600c5d4b0faf3a9589ccfc7ecd2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/9959617https://doaj.org/toc/1875-919XTo explore the application of self-efficacy in X-ray image analysis based on deep convolutional neural network (DCNN) in the care and treatment of osteoporosis patients with rheumatoid arthritis. In this study, 90 patients with osteoporosis were divided into the control group and the experimental group for DCNN combined with X-ray diagnosis. Patients in the control group were given routine nursing care, and those in the experimental group were given comprehensive nursing care. The bone mineral content, self-efficacy, anxiety, and depression in the femur and lumbar spine after care were compared. The results showed that the accuracy, sensitivity, and false-negative rate of X-ray image recognition of osteoporosis based on DCNN were 91%, 98%, and 2%, respectively. The bone mineral contents of femur and lumbar vertebra in the experimental group were significantly higher than those in the control group (P<0.05). The anxiety, depression, and self-efficacy scores of patients in the experimental group were significantly higher than those in the control group (P<0.05). In conclusion, the accuracy rate of DCNN combined with X-ray plain film imaging in the detection of osteoporosis is high. Comprehensive nursing intervention can improve the curative effect and self-efficacy of patients. The improvement of self-efficacy is a related factor for the improvement of patients’ negative emotions and quality of life.Yaqin GengTing LiuYu DingWei LiuJiayi YeLinlin HuLi RuanHindawi LimitedarticleComputer softwareQA76.75-76.765ENScientific Programming, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer software QA76.75-76.765
spellingShingle	Computer software QA76.75-76.765 Yaqin Geng Ting Liu Yu Ding Wei Liu Jiayi Ye Linlin Hu Li Ruan Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing
description	To explore the application of self-efficacy in X-ray image analysis based on deep convolutional neural network (DCNN) in the care and treatment of osteoporosis patients with rheumatoid arthritis. In this study, 90 patients with osteoporosis were divided into the control group and the experimental group for DCNN combined with X-ray diagnosis. Patients in the control group were given routine nursing care, and those in the experimental group were given comprehensive nursing care. The bone mineral content, self-efficacy, anxiety, and depression in the femur and lumbar spine after care were compared. The results showed that the accuracy, sensitivity, and false-negative rate of X-ray image recognition of osteoporosis based on DCNN were 91%, 98%, and 2%, respectively. The bone mineral contents of femur and lumbar vertebra in the experimental group were significantly higher than those in the control group (P<0.05). The anxiety, depression, and self-efficacy scores of patients in the experimental group were significantly higher than those in the control group (P<0.05). In conclusion, the accuracy rate of DCNN combined with X-ray plain film imaging in the detection of osteoporosis is high. Comprehensive nursing intervention can improve the curative effect and self-efficacy of patients. The improvement of self-efficacy is a related factor for the improvement of patients’ negative emotions and quality of life.
format	article
author	Yaqin Geng Ting Liu Yu Ding Wei Liu Jiayi Ye Linlin Hu Li Ruan
author_facet	Yaqin Geng Ting Liu Yu Ding Wei Liu Jiayi Ye Linlin Hu Li Ruan
author_sort	Yaqin Geng
title	Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing
title_short	Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing
title_full	Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing
title_fullStr	Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing
title_full_unstemmed	Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing
title_sort	deep learning-based self-efficacy x-ray images in the evaluation of rheumatoid arthritis combined with osteoporosis nursing
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/9ae4d3600c5d4b0faf3a9589ccfc7ecd
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Deep Learning-Based Self-Efficacy X-Ray Images in the Evaluation of Rheumatoid Arthritis Combined with Osteoporosis Nursing

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