This introductory tutorial is designed to equip participants with practical skills and knowledge for performing survival analysis using machine learning techniques. Survival analysis, a fundamental statistical method in biomedical and clinical research, focuses on analyzing time-to-event data, such as the time to disease progression or patient survival. In this tutorial, attendees will work with clinical and gene expression data to build, train, and test survival models. They will learn how to leverage R's mlr3 ecosystem for efficient model development, incorporating sophisticated machine learning models such as penalized linear models and random forests to enhance the accuracy of the survival predictions. Participants will also explore survival metrics and model validation techniques to assess the quality and reliability of their models in the context of real-world data. Whether you're new to survival analysis or seeking to enhance your skills, this workshop offers valuable insights and hands-on experience for tackling challenging clinical and biomedical questions.
Requirements for participating:- Bring a laptop with the latest version of R installed: https://www.r-project.org/
- Install the following libraries after 1 July (to ensure you have the latest version):
- Install some models that we will try:
- glmnet (CRAN) [Required]
- ranger (CRAN) [Optional]
- CoxBoost (GitHub) [Optional]
- aorsf (GitHub) [Optional]
References:- [1] Bischl, B., Sonabend, R., Kotthoff, L., & Lang, M. (Eds.). (2024). "Applied Machine Learning Using mlr3 in R". CRC Press. https://mlr3book.mlr-org.com
- [2] Sonabend, R., Király, F. J., Bender, A., Bischl, B., & Lang, M. (2021). mlr3proba: an R package for machine learning in survival analysis. Bioinformatics, 37(17), 2789–2791. https://doi.org/10.1093/BIOINFORMATICS/BTAB039
- [3] Zhao, Z., Zobolas, J., Zucknick, M., & Aittokallio, T. (2024). Tutorial on survival modeling with applications to omics data. Bioinformatics. https://doi.org/10.1093/BIOINFORMATICS/BTAE132 [Tutorial link]
Registration:To add this tutorial to your registration,
log in to your existing registration, click the Modify Registration button, and navigate to the Reg Options page (page 4). Select the tutorial you want to attend.