michael-lash / HITL-Sepsis-OO

Human-in-the-Loop Sepsis Outcome Optimization

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Human-in-the-Loop Sepsis Outcome Optimization (HITL-Sepsis-OO)

The code contained in this repository was used to conduct the experiments presented in the paper Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence. If you make use of this code in your research, please cite both of the following:

[1] Gupta, Akash, Lash, Michael T., and Nachimuthu, Senthil K.. "Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence." Expert Systems with Applications. Springer, 2020.

[2] Lash, Michael T., Lin, Qihan, Street, W. Nick, & Robinson, Jennifer G.. "A budget-constrained inverse classification framework for smooth classifiers." 2017 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2017.

About

Human-in-the-Loop Sepsis Outcome Optimization

License:MIT License