Analysis of treatment effect of acupuncture on cervical spondylosis and neck pain with the data mining technology under deep learning
Autor: | Yigang Chang, Yu Tang, Huaying Huo |
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Rok vydání: | 2021 |
Předmět: |
Neck pain
Computer science medicine.medical_treatment computer.software_genre medicine.disease Group B Theoretical Computer Science Hardware and Architecture Sample size determination McGill Pain Questionnaire medicine Cervical spondylosis Acupuncture Bloodletting Treatment effect Data mining medicine.symptom computer Software Information Systems |
Zdroj: | The Journal of Supercomputing. 78:5547-5564 |
ISSN: | 1573-0484 0920-8542 |
Popis: | This study was to explore the value of data mining model in evaluating the treatment effect of acupuncture on patients with cervical spondylosis (CS) and neck pain. A total of 270 patients with CS and neck pain recruited in the acupuncture clinic of Shanxi Provincial People’s Hospital were selected as the research objects in this study and were divided into an acupuncture needle group (group A), an acupoint latent acupuncture group (group B), and a puncture bloodletting group (group C) randomly, with 90 cases in each group. The Northwick Park Questionnaire (NPQ), McGill Pain Questionnaire (MPQ), and Role-Physical (RP), Physiological Function (PF), General Health (GH), and Body Pain (BP) of all patients were recorded before treatment, at the completion of the fifth acupuncture, at the end of treatment, one-month follow-up, two-month follow-up, and three-month follow-up to analyse the clinical treatment effect. Based on the artificial neural network (ANN) algorithm, a curative effect evaluation method and data mining model was further established to compare the accuracy rate of data processing by different data models, and the data processed by the data mining model were compared with the clinical data to analyse the feasibility of the data mining model. The test results found that the NPQ and MPQ values of patients in group B were significantly lower than those in groups A and C (P |
Databáze: | OpenAIRE |
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