survex: an R package for explaining machine learning survival models

• URL: http://arxiv.org/abs/2308.16113v2
• Date: Tue, 21 Nov 2023 15:50:05 GMT
• Title: survex: an R package for explaining machine learning survival models
• Authors: Miko{\l}aj Spytek and Mateusz Krzyzi\'nski and Sophie Hanna Langbein and Hubert Baniecki and Marvin N. Wright and Przemys{\l}aw Biecek
• Abstract summary: We introduce the survex R package, which provides a framework for explaining any survival model by applying artificial intelligence techniques. The capabilities of the proposed software encompass understanding and diagnosing survival models, which can lead to their improvement.
• Score: 8.028581359682239
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Due to their flexibility and superior performance, machine learning models frequently complement and outperform traditional statistical survival models. However, their widespread adoption is hindered by a lack of user-friendly tools to explain their internal operations and prediction rationales. To tackle this issue, we introduce the survex R package, which provides a cohesive framework for explaining any survival model by applying explainable artificial intelligence techniques. The capabilities of the proposed software encompass understanding and diagnosing survival models, which can lead to their improvement. By revealing insights into the decision-making process, such as variable effects and importances, survex enables the assessment of model reliability and the detection of biases. Thus, transparency and responsibility may be promoted in sensitive areas, such as biomedical research and healthcare applications.

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