Metabolic syndrome prediction model using Bayesian optimization and XGBoost based on traditional Chinese medicine features

Metabolic syndrome prediction model using Bayesian optimization and XGBoost based on traditional Chinese medicine features

Metabolic syndrome (MetS) has a high prevalence and is prone to many complications. However, current MetS diagnostic methods require blood tests that are not conducive to self-testing, so a user-friendly and accurate method for predicting MetS is needed to facilitate early detection and treatment. I...

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Bibliographic Details
Main Authors: Jianhua Zheng, Zihao Zhang, Jinhe Wang, Ruolin Zhao, Shuangyin Liu, Gaolin Yang, Zhengjie Liu, Zhengyuan Deng
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Heliyon
Subjects:
XGBoost
Machine learning
Metabolic syndrome
Traditional Chinese medicine (TCM)
Bayesian optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023099358

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http://www.sciencedirect.com/science/article/pii/S2405844023099358

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