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Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction
This study aimed to explore the application value of multifeature fusion classification algorithm based on deep learning and Yishen Tiaodu acupuncture in the diagnosis and treatment of patients with cerebral infarction in convalescence. Methods. 62 patients with cerebral infarction were randomly cla...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159848/ https://www.ncbi.nlm.nih.gov/pubmed/35665277 http://dx.doi.org/10.1155/2022/3592145 |
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author | Feng, Zhuo Hu, Miaomiao Yuan, Wei Zhao, Xiaojun Zeng, Jiazhi Zhou, Kaibin |
author_facet | Feng, Zhuo Hu, Miaomiao Yuan, Wei Zhao, Xiaojun Zeng, Jiazhi Zhou, Kaibin |
author_sort | Feng, Zhuo |
collection | PubMed |
description | This study aimed to explore the application value of multifeature fusion classification algorithm based on deep learning and Yishen Tiaodu acupuncture in the diagnosis and treatment of patients with cerebral infarction in convalescence. Methods. 62 patients with cerebral infarction were randomly classified into the experimental group and the control group, with 31 patients in each group. All patients received the functional magnetic resonance imaging (fMRI) examination. The image processing method was the multifeature fusion classification algorithm based on deep learning. DICE coefficient, accuracy, and sensitivity were used to evaluate the image processing performance of traditional and new algorithms. Patients in the experimental group were treated with Yishen Tiaodu acupuncture, while patients in the control group were treated with ordinary acupuncture. The evaluation of the cyberchondria severity scale (CSS) and the activities of daily living (ADL) was performed at enrollment, 15 days after treatment, 28 days after treatment, and 1 month after treatment. The results showed that the quality of fMRI images processed by multifeature fusion classification algorithm based on deep learning was signally improved. The clinical efficacy of the traditional Chinese medicine (TCM) syndrome score (86.7% vs. 60.9%) and neurological impairment score (83.4% vs. 53.5%) in the experimental group were remarkably higher compared with the control group (P < 0.05). After treatment, the TCM syndrome score of the experimental group was markedly lower than that of the control group, while the ADL score was higher (P < 0.05). Conclusion. The performance of multifeature fusion classification algorithm based on deep learning in fMRI image processing of patients with cerebral infarction is better than that of traditional algorithms. Yishen Tiaodu acupuncture has a good therapeutic effect on the recovery of motor and neurological function in patients with cerebral infarction at convalescence. |
format | Online Article Text |
id | pubmed-9159848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-91598482022-06-02 Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction Feng, Zhuo Hu, Miaomiao Yuan, Wei Zhao, Xiaojun Zeng, Jiazhi Zhou, Kaibin Comput Intell Neurosci Research Article This study aimed to explore the application value of multifeature fusion classification algorithm based on deep learning and Yishen Tiaodu acupuncture in the diagnosis and treatment of patients with cerebral infarction in convalescence. Methods. 62 patients with cerebral infarction were randomly classified into the experimental group and the control group, with 31 patients in each group. All patients received the functional magnetic resonance imaging (fMRI) examination. The image processing method was the multifeature fusion classification algorithm based on deep learning. DICE coefficient, accuracy, and sensitivity were used to evaluate the image processing performance of traditional and new algorithms. Patients in the experimental group were treated with Yishen Tiaodu acupuncture, while patients in the control group were treated with ordinary acupuncture. The evaluation of the cyberchondria severity scale (CSS) and the activities of daily living (ADL) was performed at enrollment, 15 days after treatment, 28 days after treatment, and 1 month after treatment. The results showed that the quality of fMRI images processed by multifeature fusion classification algorithm based on deep learning was signally improved. The clinical efficacy of the traditional Chinese medicine (TCM) syndrome score (86.7% vs. 60.9%) and neurological impairment score (83.4% vs. 53.5%) in the experimental group were remarkably higher compared with the control group (P < 0.05). After treatment, the TCM syndrome score of the experimental group was markedly lower than that of the control group, while the ADL score was higher (P < 0.05). Conclusion. The performance of multifeature fusion classification algorithm based on deep learning in fMRI image processing of patients with cerebral infarction is better than that of traditional algorithms. Yishen Tiaodu acupuncture has a good therapeutic effect on the recovery of motor and neurological function in patients with cerebral infarction at convalescence. Hindawi 2022-05-25 /pmc/articles/PMC9159848/ /pubmed/35665277 http://dx.doi.org/10.1155/2022/3592145 Text en Copyright © 2022 Zhuo Feng et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Feng, Zhuo Hu, Miaomiao Yuan, Wei Zhao, Xiaojun Zeng, Jiazhi Zhou, Kaibin Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction |
title | Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction |
title_full | Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction |
title_fullStr | Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction |
title_full_unstemmed | Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction |
title_short | Classification Algorithm-Based fMRI Images for Evaluating the Effect of Yishen Tiaodu Acupuncture on the Recovery Period of Cerebral Infarction |
title_sort | classification algorithm-based fmri images for evaluating the effect of yishen tiaodu acupuncture on the recovery period of cerebral infarction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159848/ https://www.ncbi.nlm.nih.gov/pubmed/35665277 http://dx.doi.org/10.1155/2022/3592145 |
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