Analysis of treatment effect of acupuncture on cervical spondylosis and neck pain with the data mining technology under deep learning

Huo, Huaying; Chang, Yigang; Tao, Yu

doi:10.1007/s11227-021-03959-2

Cited by 14 publications

(10 citation statements)

References 36 publications

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“…Zhang studied the definition of data mining technology, obtained the steps and methods of data mining technology, and analyzed its application in the badminton court tactical analysis system [2]. Huo et al studied the value of data mining models in evaluating the therapeutic effect of acupuncture on cervical spondylosis and neck pain patients [3]. Song took the research and application of data mining technology in book copyright information management decision-making system as the theme, and studied the role of data mining technology in book copyright information management [4].…”

Section: Related Workmentioning

confidence: 99%

“…The incorporation of fibers can improve the crack morphology, making the components more cracked, and multiple fine and dense cracks will be formed [17]. (3) Increase the deformation capacity. The fiber-reinforced concrete can continue to bear a certain load even if there are many and dense cracks when it is bent and pulled.…”

Section: Nanoscale Carbon Fiber Concretementioning

confidence: 99%

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Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

Dong

2022

Advances in Materials Science and Engineering

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The finite element method divides the existing solid structure into a finite number of elements. It integrates and analyzes the divided elements according to preset criteria, and then solves the equilibrium equation of the overall structure according to the corresponding boundary conditions. The problem is analyzed through a finite element model. A large amount of data from the experiment are derived, and then data mining technique is used to find out the data that are useful for the experiment. The purpose of this paper is to test bridge engineering through data mining technology, and then simulate different fiber-reinforced concrete models through finite element method. In this paper, three kinds of nanofibers, carbon fiber (CFRP), glass fiber (GFRP), and aramid fiber (AFRP) are used to make concrete bridges. Loading experiments are also carried out with different degrees of load on the bridge and 100 experiments on the error interval. The experimental results show that the displacement is proportional to the load to a certain extent. The carbon fiber concrete has a stronger positive correlation than the other two materials. Its finite element simulation experimental data have 78% error difference between 0 and 10, while the other two are around 40%.

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Section: Related Workmentioning

confidence: 99%

Section: Nanoscale Carbon Fiber Concretementioning

confidence: 99%

Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

Dong

2022

Advances in Materials Science and Engineering

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“…The early symptoms of CSM are not obvious; thus, most patients already have had obvious limb symptoms at the first time of hospital visit, which eventually leads to serious disablement. CSM is also one of the most common causes of adult spastic paraplegia, which greatly reduces the quality of life of patients and brings a huge economic burden to families and society [ 1 , 2 ]. With the change of work style and the aggravation of population aging in recent years, the number of CSM patients has gradually increased accompanied by a younger trend, which has attracted the attention of medical practitioners all over the world [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Relationship between Severity of Disease and Postoperative Neurological Recovery in Patients with Cervical Spondylotic Myelopathy Combined with Developmental Spinal Stenosis

Wang

Zhang

Peng

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Objective. The study aimed to investigate the correlation between the severity of disease and postoperative neurological recovery in patients with cervical spondylotic myelopathy (CSM) combined with developmental spinal stenosis. Methods. A retrospective analysis of the clinical data of 114 CSM patients combined with developmental spinal stenosis admitted to our hospital from June 2019 to June 2020 was performed. All of the patients who underwent posterior cervical unidoor vertebroplasty were divided into the mild, moderate, and severe groups according to the Torg–Pavlov ratio. The clinical data including patients’ age, course of spinal cord high signal change, and first onset age were collected. The recovery time, preoperative, and postoperative Japanese Orthopaedic Association (JOA) scores of patients in each group were compared with the calculation of the improvement rate. The correlation between the severity of disease and postoperative neurological recovery in CSM patients combined with developmental spinal stenosis was analyzed by Pearson correlation. The factors influencing postoperative neurological recovery were analyzed using multivariate logistic regression analysis. The receiver operating characteristic curve (AUC) was used to evaluate the value of each influencing factor in predicting postoperative recovery. Results. Significant differences were observed in the proportion of linear hyperintensity changes in the spinal cord, the age of first onset, the course of the disease, and the Torg–Pavlov ratio among the mild, moderate, and severe groups ( P < 0 . 05 ). The postoperative recovery time of the moderate and severe groups was significantly higher than that of the mild group, while the preoperative JOA score was significantly lower than that of the mild group. On the other hand, the postoperative recovery time of the severe group was prominently higher than that of the moderate group, whereas the preoperative JOA score was observably lower than that of the moderate group ( P < 0 . 05 ). Pearson correlation analysis showed that the postoperative recovery time was significantly negatively correlated with the Torg–Pavlov ratio, age at first onset, and disease course (r = −0.359, −0.502, −0.368, P < 0 . 05 ), while it was positively correlated with spinal cord linear high-signal changes (r = 0.641, P < 0 . 05 ). Multifactorial logistic regression analysis revealed that the Torg–Pavlov ratio, age at first onset, and disease course were protective factors, while spinal cord linear high-signal alterations were risk factors affecting the recovery time of postoperative neurological function ( P < 0 . 05 ). The area under the curve (AUC) of the Torg–Pavlov ratio, linear hyperintensity changes in the spinal cord, age at first onset, and disease duration in predicting the postoperative neurological recovery time were 0.794, 0.767, 0.772, and 0.802, respectively. The AUC predicted by the combined detection of each factor was 0.876, which was better than the area under the curve of single prediction. Conclusion. Patients with CSM combined with developmental spinal stenosis were characterized by younger age of onset, a short course of the disease, and linear changes in the spinal cord high signal. The degree of developmental spinal stenosis may affect the postoperative recovery time of neurological function in CSM patients but had little effect on postoperative neurological recovery. The Torg–Pavlov ratio, age of first onset, course of the disease, and changes in the spinal cord linear hyperintensity were the factors that affected postoperative neurological recovery, which may provide a basis for reasonably predicting a postoperative neurological recovery in patients with CSM combined with developmental spinal stenosis.

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“…Even the ideological education of students in colleges and universities and the thoughts of relevant managers at all levels of society have been impacted to a certain extent. In the face of the current internal and external environment, how to give better play to the functions of ideological education and mental health education in Colleges and Universities under the premise of correctly understanding the current economic, cultural and other social phenomena, and guide students to correct themselves in the increasingly complex society is the key to mental health teaching in Colleges and universities [2]. us, this article describes the design of college psychology instruction management based on information technology, as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

The Architecture of College Psychological Teaching Management System Based on Data Mining Technology

Huang

Leng

2022

Security and Communication Networks

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In order to meet the requirements of the development of educational informatization, combined with data mining technology, this article studies the architecture of the college psychological teaching management system. To experience the benefits brought by the Internet age, in order to further improve performance and meet the needs of the Internet information age, many colleges and universities have begun to strengthen the development of teaching management. Based on this background, this article proposes a standardized mode of mental health management in colleges and universities based on information technology. With the help of data warehouse and data mining technology, the ID3 algorithm, organizational rules, and other algorithms are used to develop a psychology subject evaluation system. Based on the improvement of grades and the behavioral characteristics of college students, this article formulates cross-platform operation rules, determines the B/S type as the normal state, and solves the best problem through comparison and selection. Then, a more specific system architecture design is carried out. The architecture of the software system selects the classic three-tier structure, which makes the client independent of the use platform and meets the requirements of user diversity and system portability. The design of functional modules such as the system fully meets the requirements of the ideological education management system for college students in the above analysis, with reasonable structure and clear logic. Finally, the advantages of the designed system architecture are summarized, including clarifying the grading idea of ideological education and training. It expands the transplantation ability of the system in a cross-platform way.

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Analysis of treatment effect of acupuncture on cervical spondylosis and neck pain with the data mining technology under deep learning

Cited by 14 publications

References 36 publications

Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

Relationship between Severity of Disease and Postoperative Neurological Recovery in Patients with Cervical Spondylotic Myelopathy Combined with Developmental Spinal Stenosis

The Architecture of College Psychological Teaching Management System Based on Data Mining Technology

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