scikit-survival: A Library for Time-to-Event Analysis Built on Top of scikit-learn

Abstract

scikit-survival is an open-source Python package for time-to-event analysis fully compatible with scikit-learn. It provides implementations of many popular machine learning techniques for time-to-event analysis, including penalized Cox model, Random Survival Forest, and Survival Support Vector Machine. In addition, the library includes tools to evaluate model performance on censored time-to-event data. The documentation contains installation instructions, interactive notebooks, and a full description of the API. scikit-survival is distributed under the GPL-3 license with the source code and detailed instructions available at https://github.com/sebp/scikit-survival
Publication
Journal of Machine Learning Research
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Sebastian Pölsterl
Post-Doctoral Researcher

My research interests include machine learning for time-to-event analysis, non-Euclidean data, and biomedical applications.