Previously submitted to: JMIR Medical Informatics (no longer under consideration since Jun 22, 2021)
Date Submitted: Mar 5, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Intelligent Optimization of Treatment of Acupuncture based on Modern Data Analysis
ABSTRACT
In this study, the acupuncture and moxibustion in traditional Chinese medicine were combined to optimize the formation of warm acupuncture therapy, and then the research on warm acupuncture was optimized using modern data analysis methods. At first, the statistics of personal information and operation of 60 patients with breast cancer was carried out. The statistical results were analyzed by rank sum test and independent sample T test. The results showed that there was no significant difference between the two groups (P>0.05), which was comparable. Then, the patient's fatigue degree, mental state and fatigue state were statistically analyzed by visual analogue scale (VAS), brief profile of mood state (BPOMS) and identity-consequence fatigue scale (ICFS). The independent T test method and paired T test method were used to analyze the results of the same time point of different groups and the same group of different time points. It was found that warm acupuncture has a significant improvement effect on POFS symptoms (P<0.05). Through blood analysis of patients, it was found that warm acupuncture can also significantly improve the nutritional status of patients after surgery (P<0.05).
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