This dataset contains in-silico results of insulin treatment using a fully automated artificial pancreas algorithm based on reinforcement learning for FDA-approved virtual patients (C. D. Man et al., 2014) with type 1 diabetes (10 adults and 10 adolescents). 

DOI Link: 
10.21227/z0nt-z923
Read more

Dataset Files

You must be an IEEE Dataport Subscriber to access these files. Subscribe now or login.

[1] Seunghyun Lee, "Fully automated insulin treatment", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/z0nt-z923. Accessed: Jan. 17, 2025.
@data{z0nt-z923-19,
doi = {10.21227/z0nt-z923},
url = {http://dx.doi.org/10.21227/z0nt-z923},
author = {Seunghyun Lee },
publisher = {IEEE Dataport},
title = {Fully automated insulin treatment},
year = {2019} }
TY - DATA
T1 - Fully automated insulin treatment
AU - Seunghyun Lee
PY - 2019
PB - IEEE Dataport
UR - 10.21227/z0nt-z923
ER -
Seunghyun Lee. (2019). Fully automated insulin treatment. IEEE Dataport. http://dx.doi.org/10.21227/z0nt-z923
Seunghyun Lee, 2019. Fully automated insulin treatment. Available at: http://dx.doi.org/10.21227/z0nt-z923.
Seunghyun Lee. (2019). "Fully automated insulin treatment." Web.
1. Seunghyun Lee. Fully automated insulin treatment [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/z0nt-z923
Seunghyun Lee. "Fully automated insulin treatment." doi: 10.21227/z0nt-z923