Abstract

Dementia in Parkinson's disease (PD) has become a major factor affecting the quality of life of patients with Parkinson's disease. Early detection and timely prevention can delay the progression of dementia, improve the quality of life of patients, and reduce the burden on society. This article is aimed at studying how to analyze the efficacy of moxibustion in the treatment of Parkinson's disease through meta-analysis on the basis of smart medicine. This article puts forward the related conceptual knowledge of smart medicine and meta-analysis and moxibustion treatment and proposes a deep learning method based on smart medicine to analyze the effects of moxibustion treatment on patients. The experiment in this article can be seen from the data in one of the figures that the highest curative effect of using a single moxibustion to treat Parkinson's disease is about 46%, while the curative effect of using a combination of moxibustion and Western medicine has reached 90%. It can be seen that a single moxibustion is not as effective as a combination of the two for Parkinson's disease. From the data in one of the tables, it can be seen that the proportion of Parkinson's disease in 2016 was 15%, showing an increase of 5%. By 2020, the proportion of Parkinson's disease was as high as 38%, and the growth rate reached 9%. It can be seen that the prevalence of this disease is getting higher and higher. Parkinson's disease has caused many undesirable effects on patients, such as slow movement, mental disorders, and a decline in mental state. Therefore, it is urgent to study the treatment of Parkinson's disease. Moxibustion can improve the patient's blood circulation and help the patient's local limbs to recover more easily and can help improve the patient's motor function.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.