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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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Autori principali: Jianhua Zheng, Zihao Zhang, Jinhe Wang, Ruolin Zhao, Shuangyin Liu, Gaolin Yang, Zhengjie Liu, Zhengyuan Deng
Natura: Artigo
Lingua:Inglês
Pubblicazione: Elsevier 2023-12-01
Serie:Heliyon
Soggetti:
XGBoost
Machine learning
Metabolic syndrome
Traditional Chinese medicine (TCM)
Bayesian optimization
Accesso online:http://www.sciencedirect.com/science/article/pii/S2405844023099358
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