icu-sepsis 2.0.1

Python implementation of the ICU-Sepsis environment.

The ICU-Sepsis Environment

The ICU-Sepsis environment is a reinforcement learning environment that simulates the treatment of sepsis in an intensive care unit (ICU).

Environment description

ICU-Sepsis is a tabular MDP with $N_S = 716$ states ($\{0,1,\dots,715\}$) and $N_A = 25$ actions ($\{0,1,\dots,24\}$). Each episode simulates the treatment of one sepsis patient in the ICU.

An episode ends when the patient survives (state $714$) and gets a reward of +1, or dies (state $713$) and gets a reward of 0, while all the intermediate rewards are 0. The discount factor is set as $\gamma = 1$.

Baselines

Some baseline results are shown below as a reference.

	Random	Expert	Optimal
Avg. return	0.78	0.78	0.88
Avg. episode length	9.45	9.22	10.99

The three baseline policies used are:

1. Random: Each action is taken uniformly randomly out of all the actions in any given state.
2. Expert: The estimated policy used by clinicians in the real world, computed using the data from the MIMIC-III dataset.
3. Optimal: Optimal policy computed using value iteration (requires knowledge of the transition parameters)

Admissible actions

In the MIMIC-III dataset, not all actions are taken enough times in each state to reliably estimate the transition probabilities, and such actions are considered inadmissible. To deal with this issue, the transition probabilities for inadmissible actions are set to the mean of the transition probabilities of all admissible actions in the state. This way, the environment can be used with all actions in all states. This is an implementation detail and does not need to be considered for normal use. See the paper for more details.

Installation

ICU-Sepsis can be used with Python 3.10 or later, with gymnasium 0.28.1 or later, and gym 0.21.0 or later. The environment can be installed using the pip command:

pip install icu-sepsis

Uninstallation

To uninstall, use the pip uninstall command:

pip uninstall icu_sepsis -y

Quickstart

The environment can be loaded with the Gym or Gymnasium packages and follows the standard Gym API. The following code snippet demonstrates how to create the environment, reset it, and take a step:

import gymnasium as gym
import icu_sepsis

env = gym.make('Sepsis/ICU-Sepsis-v2')

state, info = env.reset()
print('Initial state:', state)
print('Extra info:', info)

next_state, reward, terminated, truncated, info = env.step(0)
print('\nTaking action 0:')
print('Next state:', next_state)
print('Reward:', reward)
print('Terminated:', terminated)
print('Truncated:', truncated)

You can also run the script examples/quickstart.py to verify that the installation was successful.

Version 2 changes

As mentioned previously, not all actions are admissible in all states, so the transition probabilities for inadmissible actions are set to the mean of the transition probabilities of all admissible actions in the state. This was the only mode of operation in version 1, and all the baseline numbers are based on this mode.

In version 2, this mode remains the default, so creating the environment with gym.make('Sepsis/ICU-Sepsis-v2') without providing any additional arguments is equivalent to the version 1 behavior.

However, in version 2, the environment creation can take an optional argument inadmissible_action_strategy which can be set to the following values:

1. 'mean' (default): The transition probabilities for inadmissible actions are set to the mean of the transition probabilities of all admissible actions in the state.
2. 'terminate': The environment terminates the episode if an inadmissible action is taken in any state, and the patient is sent to the "death" state.
3. 'raise_exception': The environment raises an exception if an inadmissible action is taken in any state.