The UVA/PADOVA Type 1 Diabetes Simulator
By Chiara Dalla Man, Francesco Micheletto, Dayu Lv, M. Breton, Boris P. Kovatchev, Claudio Cobelli. 2014
807 citations recorded by the source corpus.
Subfields: Endocrinology, Diabetes and Metabolism, Genetics, Surgery, Medical & Health AI
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Endocrinology, Diabetes and Metabolism
In Genetics
- Philip S. Thomas
- Bruno Castro da Silva
- Georgios Theocharous
- Andrew Barto
- Emma Brunskill
- Jacob Steinhardt
In Surgery
In Medical & Health AI
Citations in the corpus
- The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models (2022, background): “It extends a FDA-approved simulator (Man et al., 2014) for blood glucose levels of a patient with Type 1 diabetes.”
- Towards Safe Policy Improvement for Non-Stationary MDPs (2020, neutral): “Non-Stationary Diabetes Treatment: This environment is based on an open-source implementation [68] of the FDA approved Type-1 Diabetes Mellitus simulator (T1DMS) [44, 37] for treatment of Type-1 diabetes.”
- Optimizing for the Future in Non-Stationary MDPs (2020, methodology): “This environment is based on an open-source implementation (Xie, 2019) of the FDA approved Type-1 Diabetes Mellitus simulator (T1DMS) (Man et al., 2014) for treatment of Type-1 Diabetes.”
- On Ensuring that Intelligent Machines Are Well-Behaved (2017, methodology): “ H . Figure 2 shows the result of applying both our Seldonian algorithm and a similar algorithm designed using the standard approach. For this experiment we used a detailed metabolic simulator [Dalla Man et al., 2014]. Given the recent surge of real-world machine learning applications and the corres”
- Universal Off-Policy Evaluation (2021, methodology): “To do so, we use the following domains: (1) An open source implementation [102] of the FDA-approved type-1 diabetes treatment simulator [59], (2) A stationary and a non-stationary recommender system domain, and (3) A continuous-state Gridworld with partial observability, where data is collected usin”