GillesPy: a Python package for stochastic model building and simulation

J.H. Abel, B. Drawert, A. Hellander, and L.R. Petzold, “GillesPy: a Python package for stochastic model building
and simulation,” IEEE Life Sciences Letters, 2017. doi: 10.1109/LLS.2017.2652448

Intraperitoneal Insulin Delivery Provides Superior Glycemic Regulation to Subcutaneous Insulin Delivery in Model Predictive Control‐based Fully‐automated Artificial Pancreas in Patients with Type 1 Diabetes: A Pilot Study

Dassau, E., Renard, E., Place, J., Farret, A., Pelletier, M.J., Lee, J., Huyett, L.M., Chakrabarty, A., Doyle III, F.J. and Zisser, H.C. “Intraperitoneal Insulin Delivery Provides Superior Glycemic Regulation to Subcutaneous Insulin Delivery in Model Predictive Control‐based Fully‐automated Artificial Pancreas in Patients with Type 1 Diabetes: A Pilot Study.” Diabetes, Obesity and Metabolism, 2017. doi: 10.1111/dom.12999

Feasibility of long-term closed-loop control: a multicenter 6-month trial of 24/7 automated insulin delivery

Kovatchev, B., Cheng, P., Anderson, S.M., Pinsker, J.E., Boscari, F., Buckingham, B.A., Doyle III, F.J., Hood, K.K., Brown, S.A., Breton, M.D. and Chernavvsky, D. “Feasibility of long-term closed-loop control: a multicenter 6-month trial of 24/7 automated insulin delivery.” Diabetes Technology & Therapeutics, vol. 19, no. 1, 2017.

An Enhanced Model Predictive Control for the Artificial Pancreas Using a Confidence Index Based on Residual Analysis of Past Predictions

A.J. Laguna-Sanz, F.J. Doyle III, and E. Dassau. “An Enhanced Model Predictive Control for the Artificial Pancreas Using a Confidence Index Based on Residual Analysis of Past Predictions.” Journal of Diabetes Science and Technology, 2016. doi: 10.1177/1932296816680632

A systems theoretic approach to analysis and control of mammalian circadian dynamics

J.H. Abel and F.J. Doyle III. “A systems theoretic approach to analysis and control of mammalian circadian dynamics.” Chemical Engineering Research and Design, 2016. doi:10.1016/j.cherd.2016.09.033

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

S. Zavitsanou, A. Chakrabarty, E. Dassau, and F.J. Doyle III. “Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas.” Processes 4(4), 35, 2016. doi:10.3390/pr4040035

Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes.

R. Gondhalekar, E. Dassau, and F.J. Doyle III. “Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes.” Automatica 71: 237-246, 2016. doi:10.1016/j.automatica.2016.04.015

A multi-metric evaluation of stratifi ed random sampling for classification: a case study.

G.S. Thakur, B.J. Daigle Jr, M. Qian, K.R. Dean, Y. Zang, R. Yang, T.K. Kim, X. Wu, L.R. Petzold, F.J. Doyle III. IEEE Life Sciences Letters vol. 1, no 2. doi: 10.1109/LLS.2016.2615086,

Metric focused feature selection for customized biomarker identi cation in Breast Cancer.

In Proceedings of Foundations of Systems Biology in Engineering (FOSBE), 2015.

Outcome Measures for Artificial Pancreas Clinical Trials: A Consensus Report.

D.M. Maahs, B.A. Buckingham, J.R. Castle, A. Cinar, E.R. Damiano, E. Dassau, J.H. DeVries, F.J. Doyle III, S.C. Griffen, A. Haidar, L. Heinemann, R. Hovorka, T.W. Jones, C. Kollman, B. Kovatchev, B.L. Levy, R. Nimri, D.N. O’Neal, M. Philip, E. Renard, S.J. Russell, S.A. Weinzimer, H. Zisser, J.W. Lum. Diabetes Care. 39(7):1175-9, 2016. doi: 10.2337/dc15-2716. Review.