ICU-Sepsis: A Benchmark MDP Built from Real Medical Data
<|reference_start|>ICU-Sepsis: A Benchmark MDP Built from Real Medical Data: 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.<|reference_end|>
@article{choudhary2024icu-sepsis:,
    title={ICU-Sepsis: A Benchmark MDP Built from Real Medical Data},
    author={Kartik Choudhary, Dhawal Gupta, Philip S. Thomas},
    journal={arXiv preprint arXiv:2406.05646},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.05646},
    primaryClass={cs.LG}
}