Predicting Plasmodium knowlesi transmission risk across Peninsular Malaysia using machine learning-based ecological niche modeling approaches
- 1Department of Parasitology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
- 2Disease Control Division, Ministry of Health Malaysia, Putrajaya, Malaysia
- 3Sabah State Health Department, Ministry of Health Malaysia, Kota Kinabalu, Sabah, Malaysia
- 4Department of Molecular Parasitology and Tropical Diseases, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
A corrigendum on
Predicting Plasmodium knowlesi transmission risk across Peninsular Malaysia using machine learning-based ecological niche modeling approaches
by Phang, W. K., Hamid, M. H. b. A., Jelip, J., Mudin, R. N. b., Chuang, T. –W., Lau, Y. L. and Fong, M. Y. (2023). Front. Microbiol. 14:1126418. doi: 10.3389/fmicb.2023.1126418
In the published article, there was an error in the Funding statement. “This study was supported by the Ministry of Higher Education, Malaysia Long Term Research Grant Scheme (LRGS/1/2018/UM/01/1/1) and the Ministry of Science and Technology, Taiwan (MOST108-2638-H-002-002-MY2).” The correct Funding statement appears below.
Funding
This study was supported by the Ministry of Higher Education, Malaysia Long Term Research Grant Scheme (LRGS/1/2018/UM/01/1/1) and the Ministry of Science and Technology, Taiwan (MOST110-2621-M-038-001-MY2).
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: Plasmodium knowlesi, Peninsular Malaysia, ecological niche modeling, XGBoost, ensemble modeling, maximum entropy
Citation: Phang WK, Hamid MHbA, Jelip J, Mudin RNb, Chuang T-W, Lau YL and Fong MY (2023) Corrigendum: Predicting Plasmodium knowlesi transmission risk across Peninsular Malaysia using machine learning-based ecological niche modeling approaches. Front. Microbiol. 14:1178864. doi: 10.3389/fmicb.2023.1178864
Received: 03 March 2023; Accepted: 06 March 2023;
Published: 16 March 2023.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2023 Phang, Hamid, Jelip, Mudin, Chuang, Lau and Fong. 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: Ting-Wu Chuang, chtingwu@tmu.edu.tw