Department of Acupuncture, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China.
Department of Sports, Guangxi Medical University, Nanning 530021, Guangxi, China.
Comput Intell Neurosci. 2022 May 25;2022:3592145. doi: 10.1155/2022/3592145. eCollection 2022.
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. . 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 ( < 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 ( < 0.05). . 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.
本研究旨在探讨基于深度学习和益肾调督针法的多特征融合分类算法在脑梗死恢复期患者诊断和治疗中的应用价值。将 62 例脑梗死患者随机分为实验组和对照组,每组 31 例。所有患者均接受功能磁共振成像(fMRI)检查。图像处理方法为基于深度学习的多特征融合分类算法。采用 DICE 系数、准确率和灵敏度评估传统和新算法的图像处理性能。实验组患者采用益肾调督针法治疗,对照组患者采用普通针刺治疗。在入组时、治疗后 15 天、治疗后 28 天和治疗后 1 个月进行网络成瘾严重程度量表(CSS)和日常生活活动(ADL)评估。结果表明,基于深度学习的多特征融合分类算法处理的 fMRI 图像质量得到显著改善。实验组中医证候评分(86.7%比 60.9%)和神经功能缺损评分(83.4%比 53.5%)的临床疗效显著高于对照组(<0.05)。治疗后,实验组中医证候评分明显低于对照组,ADL 评分升高(<0.05)。基于深度学习的多特征融合分类算法在脑梗死患者 fMRI 图像处理中的性能优于传统算法。益肾调督针法对脑梗死恢复期患者运动和神经功能的恢复有较好的治疗作用。