Application of Artificial Intelligence in the Establishment of an Association Model between Metabolic Syndrome, TCM Constitution, and the Guidance of Medicated Diet Care.

Pei- Li Chien,Yi-Feng Wang,Pei-Hung Liao,Hui-Ting Huang,Shih-Ming Chen,Hei-Jen Jou,Tzuu-Guang Young,Chi-Feng Liu,Shuibin Lin

doi:10.1155/2021/5530717

Abstract

Background This study conducted exploratory research using artificial intelligence methods. The main purpose of this study is to establish an association model between metabolic syndrome and the TCM (traditional Chinese medicine) constitution using the characteristics of individual physical examination data and to provide guidance for medicated diet care. Methods Basic demographic and laboratory data were collected from a regional hospital health examination database in northern Taiwan, and artificial intelligence algorithms, such as logistic regression, Bayesian network, and decision tree, were used to analyze and construct the association model between metabolic syndrome and the TCM constitution. Findings. It was found that the phlegm-dampness constitution (90.6%) accounts for the majority of TCM constitution classifications with a high risk of metabolic syndrome, and high cholesterol, blood glucose, and waist circumference were statistically significantly correlated with the phlegm-dampness constitution. This study also found that the age of patients with metabolic syndrome has been advanced, and shift work is one of the risk indicators. Therefore, based on the association model between metabolic syndrome and TCM constitution, in the future, metabolic syndrome can be predicted through the syndrome differentiation of the TCM constitution, and relevant medicated diet care schemes can be recommended for improvement. Conclusion In order to increase the public's knowledge and methods for mitigating metabolic syndrome, in the future, nursing staff can provide nonprescription medicated diet-related nursing guidance information via the prediction and assessment of the TCM constitution.

Highlights

In 2018, the Statistics Department of the Ministry of Health and Welfare of Taiwan released the top 10 causes of death: cancer and metabolic syndrome are the major threats to the health of both men and women, and they impose a great burden on health care expenditures and families [1, 2]
Among the 8,316 data collected, it was found that blood glucose before meal, total cholesterol, waist circumference, age, hypertension, and shift work were more important than other test factors. erefore, this study used these 6 high-risk factors to analyze the correlation and prediction of 4 major Traditional Chinese medicine (TCM) constitutions
According to the study of metabolic syndrome and occupational categories, as conducted in 2009 by Executive Yuan labor safety researchers, the prevalence rate of metabolic syndrome among male workers in Taiwan was 19.4%, while that among female workers was 14.8%, with the highest rates among commerce, manufacturing, and construction industries. e related risk factors were hyperglycemia, high cholesterol, sleep quality, and shift work, which are different from the results of this study. is study shows that the technology industry and shift workers suffer the most metabolic syndrome, and the main risk factors were hyperglycemia, high cholesterol, and excessive waist circumference, which may be different from changes in social patterns [38]. e results of this study are similar to the research results of other scholars

Summary

Introduction

E high-risk groups for metabolic syndrome include those with a family history of hypertension, diabetes, and dyslipidemia, which accounts for about 20%, the incidence of metabolic syndrome of whom is higher than that of the general population, and people with a dietary preference for low fiber, high sugar, high fat, and excessive alcohol consumption, as well as stress, which results in endocrine disorders and increasing blood glucose [6]. In order to achieve the goal of weight loss and thin waist circumference [8], Taiwan officially launched the metabolic syndrome prevention and control strategy in 2018, which aims at primary prevention to help people reduce the risk factors of metabolic syndrome and change their lifestyle, such as regular daily life habits, more intake of high-fiber, less oily and more healthy diet, and reducing animal fat and refined sugar intake

Methods

Results

Conclusion