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ICU-Sepsis: A Benchmark MDP Built from Real Medical Data

2024-06-09 · Kartik Choudhary, Dhawal Gupta, Philip S. Thomas

We present ICU-Sepsis, an environment that can be used in benchmarks for evaluating reinforcement learning (RL) algorithms. Sepsis management is a complex task that has been an important topic in applied RL research in recent years. Therefore, MDPs that model sepsis management can serve as part of a benchmark to evaluate RL algorithms on a challenging real-world problem. However, creating usable MDPs that simulate sepsis care in the ICU remains a challenge due to the complexities involved in acquiring and processing patient data. ICU-Sepsis is a lightweight environment that models personalized care of sepsis patients in the ICU. The environment is a tabular MDP that is widely compatible and is challenging even for state-of-the-art RL algorithms, making it a valuable tool for benchmarking their performance. However, we emphasize that while ICU-Sepsis provides a standardized environment for evaluating RL algorithms, it should not be used to draw conclusions that guide medical practice.

📄 PDF Abstract BibTeX arXiv:2406.05646

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icu-sepsis/icu-sepsis 공식 구현

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BenchmarkingManagementReinforcement Learning (RL)

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