Corrigendum: Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study

Front Public Health. 2021 Oct 29:9:778749. doi: 10.3389/fpubh.2021.778749. eCollection 2021.

Okechinyere J Achilonu¹, June Fabian^{2

3}, Brendan Bebington^{3

4}, Elvira Singh^{1

5}, Gideon Nimako^{1

6}, M J C Eijkemans⁷, Eustasius Musenge¹

¹ Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa.
² Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
³ Wits Donald Gordon Medical Centre, School of Clinical Medicine, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
⁴ Department of Surgery, Faculty of Health Science University of the Witwatersrand Faculty of Science, Parktown, Johannesburg, South Africa.
⁵ National Cancer Registry, National Health Laboratory Service, 1 Modderfontein Road, Sandringham, Johannesburg, South Africa.
⁶ Industrialization, Science, Technology and Innovation Hub, African Union Development Agency (AUDA-NEPAD), Johannesburg, South Africa.
⁷ Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht University, Utrecht, Netherlands.

Abstract

[This corrects the article DOI: 10.3389/fpubh.2021.694306.].

Keywords: cancer; colorectal; filter feature selection; machine learning; prediction; recurrence; survival.