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; Chi-Feng Liu; Hui-Ting Huang; Hei-Jen Jou; Shih-Ming Chen; Tzuu-Guang Young; Yi-Feng Wang; Pei-Hung Liao

doi:10.1155/2021/5530717

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

Evid Based Complement Alternat Med. 2021 Apr 30:2021:5530717. doi: 10.1155/2021/5530717. eCollection 2021.

Authors

Pei-Li Chien¹, Chi-Feng Liu², Hui-Ting Huang³, Hei-Jen Jou⁴, Shih-Ming Chen⁴, Tzuu-Guang Young⁵, Yi-Feng Wang⁶, Pei-Hung Liao²

Affiliations

¹ Public Affairs Office, Taiwan Adventist Hospital, No. 424, Sec. 2, Bade Road., Songshan District, Taipei City 10556, Taiwan.
² School of Nursing, National Taipei University of Nursing and Health Sciences, No. 365, Ming-te Road, Peitou District, Taipei City 112, Taiwan.
³ Department of Gastroenterology, Taiwan Adventist Hospital, No. 424, Sec. 2, Bade Road., Songshan District, Taipei City 10556, Taiwan.
⁴ Department of Obstetrics and Gynecology, Taiwan Adventist Hospital, No. 424, Sec. 2, Bade Road., Songshan District, Taipei City 10556, Taiwan.
⁵ Department of Infectious Disease, Taiwan Adventist Hospital, No. 424, Sec. 2, Bade Road., Songshan District, Taipei City 10556, Taiwan.
⁶ Health Clinic, Taiwan Adventist Hospital, No. 424, Sec. 2, Bade Road., Songshan District, Taipei City 10556, Taiwan.

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.