In the published article, Gideon Nimako was not included as an author in the published article. 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.
Summary
Keywords
colorectal, cancer, recurrence, survival, machine learning, filter feature selection, prediction
Citation
Achilonu OJ, Fabian J, Bebington B, Singh E, Nimako G, Eijkemans MJC and Musenge E (2021) Corrigendum: Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study. Front. Public Health 9:778749. doi: 10.3389/fpubh.2021.778749
Received
17 September 2021
Accepted
20 September 2021
Published
29 October 2021
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
9 - 2021
Updates
Copyright
© 2021 Achilonu, Fabian, Bebington, Singh, Nimako, Eijkemans and Musenge.
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: Okechinyere J. Achilonu achilonu.okechinyere@gmail.com
This article was submitted to Life-Course Epidemiology and Social Inequalities in Health, a section of the journal Frontiers in Public Health
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.