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CORRECTION article

Front. Public Health, 29 July 2024
Sec. Environmental Health and Exposome
Volume 12 - 2024 | https://doi.org/10.3389/fpubh.2024.1456139

Corrigendum: The relationship between heavy metals and metabolic syndrome using machine learning

This article is a correction to:

  1. The relationship between heavy metals and metabolic syndrome using machine learning

    1. Read original article
\r\nJun Yao&#x;Jun Yao1†Zhilin Du&#x;Zhilin Du2†Fuyue Yang&#x;Fuyue Yang3†Ran Duan, Ran Duan4,5*Tong Feng Tong Feng6*
  • 1Department of Respiratory and Critical Care, Guangyuan Central Hospital, Guangyuan, Sichuan, China
  • 2Department of Oncology, Chengdu Seventh People's Hospital (Affliated Cancer Hospital of Chengdu Medical College), Chengdu, Sichuan, China
  • 3Department of Rheumatology and Immunology, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China
  • 4Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
  • 5Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
  • 6The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China

A corrigendum on
The relationship between heavy metals and metabolic syndrome using machine learning

by Yao, J., Du, Z., Yang, F., Duan, R., and Feng, T. (2024). Front. Public Health 12:1378041. doi: 10.3389/fpubh.2024.1378041

In the published article, there was an error regarding the affiliations for Ran Duan. In addition to being affiliated with “Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China,” she should also be affiliated with “Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China.”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: metabolic syndrome, NHANES (National Health and Nutrition Examination Survey), machine learning, heavy metals, SHapley additive exPlanations (SHAP)

Citation: Yao J, Du Z, Yang F, Duan R and Feng T (2024) Corrigendum: The relationship between heavy metals and metabolic syndrome using machine learning. Front. Public Health 12:1456139. doi: 10.3389/fpubh.2024.1456139

Received: 28 June 2024; Accepted: 19 July 2024;
Published: 29 July 2024.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2024 Yao, Du, Yang, Duan and Feng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ran Duan, 1345295687@qq.com; Tong Feng, 543051181@qq.com

†These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.