Automated machine learning with R: AutoML tools for beginners in clinical research
10.7602/jmis.2024.27.3.129
- Author:
Youngho PARK
1
Author Information
1. Department of Big Data Application, College of Smart Interdisciplinary Engineering, Hannam University, Daejeon, Korea
- Publication Type:REVIEW ARTICLE
- From:Journal of Minimally Invasive Surgery
2024;27(3):129-137
- CountryRepublic of Korea
- Language:English
-
Abstract:
Recently, interest in machine learning (ML) has increased as the application fields have expanded significantly. Although ML methods excel in many fields, establishing an ML pipeline requires considerable time and human resources. Automated ML (AutoML) tools offer a solution by automating repetitive tasks, such as data preprocessing, model selection, hyperparameter optimization, and prediction analysis. This review introduces the use of AutoML tools for general research, including clinical studies. In particular, it outlines a simple approach that is accessible to beginners using the R programming language (R Foundation for Statistical Computing). In addition, the practical code and output results for binary classification are provided to facilitate direct application by clinical researchers in future studies.
