Factory-calibrated continuous glucose monitoring: how and why it works, and the dangers of reuse beyond approved duration of wear GP Forlenza, T Kushner, LH Messer, RP Wadwa, S Sankaranarayanan Diabetes technology & therapeutics 21 (4), 222-229, 2019 | 21 | 2019 |
Robust data-driven control of artificial pancreas systems using neural networks S Dutta, T Kushner, S Sankaranarayanan International Conference on Computational Methods in Systems Biology, 183-202, 2018 | 18 | 2018 |
A data-driven approach to artificial pancreas verification and synthesis T Kushner, D Bortz, DM Maahs, S Sankaranarayanan 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS ¡¦, 2018 | 12 | 2018 |
Multi-hour blood glucose prediction in type 1 diabetes: A patient-specific approach using shallow neural network models T Kushner, MD Breton, S Sankaranarayanan Diabetes Technology & Therapeutics 22 (12), 883-891, 2020 | 11 | 2020 |
Bursts of activity: Temporal patterns of help-seeking and support in online mental health forums T Kushner, A Sharma Proceedings of the web conference 2020, 2906-2912, 2020 | 9 | 2020 |
A new approach to feedback for robust signaling gradients T Kushner, A Simonyan, FYM Wan Studies in Applied Mathematics 133 (1), 18-51, 2014 | 9 | 2014 |
Models, devices, properties, and verification of artificial pancreas systems T Kushner, B Wayne Bequette, F Cameron, G Forlenza, D Maahs, ... Automated Reasoning for Systems Biology and Medicine, 93-131, 2019 | 8 | 2019 |
Verifying conformance of neural network models M Narasimhamurthy, T Kushner, S Dutta, S Sankaranarayanan 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-8, 2019 | 4 | 2019 |
Conformance verification for neural network models of glucose-insulin dynamics T Kushner, S Sankaranarayanan, M Breton Proceedings of the 23rd International Conference on Hybrid Systems ¡¦, 2020 | 2 | 2020 |
Sherlock: A Tool for Verification of Deep Neural Networks S Dutta, T Kushner, S Jha, S Sankaranarayanan, N Shankar, A Tiwari | 1 | |
291-OR: Using the Performance in Exercise and Knowledge (PEAK) Guidelines Incorporated in a Smartphone-Based Decision Support System Improves Glucose Outcomes during Free ¡¦ LM WILSON, PG JACOBS, FH GUILLOT, NS TYLER, T KUSHNER, ... Diabetes 71 (Supplement_1), 2022 | | 2022 |
771-P: Acceptance of Decision Support Recommendations Improves Time in Range for People Living with Type 1 Diabetes on Multiple Daily Injections JR CASTLE, AZ ESPINOZA, NS TYLER, LM WILSON, ... Diabetes 71 (Supplement_1), 2022 | | 2022 |
DIABLOCKS: MULTIVARIATE PATTERN DETECTION FOR PATIENT-SPECIFIC IDENTIFICATION AND TARGETED ADJUSTMENT OF PROBLEM PATTERNS IN DIABETES CARE MANAGEMENT T Kushner, C Mosquera-Lopez, L Wilson, D Branigan, E Wan, J Eom, ... DIABETES TECHNOLOGY & THERAPEUTICS 24, A230-A231, 2022 | | 2022 |
TRANSLATING STANDARD CLINICAL PROTOCOL INTO TUNING PROCEDURES FOR HYBRID CLOSED LOOP SYSTEMS: 670G, CONTROL-IQ AND LOOP T Kushner, G Forlenza, L Messer DIABETES TECHNOLOGY & THERAPEUTICS 22, A79-A79, 2020 | | 2020 |
MODEL CONFORMANCE IN BLOOD GLUCOSE PREDICTION TASKS T Kushner, S Sankaranarayanan, M Breton DIABETES TECHNOLOGY & THERAPEUTICS 22, A78-A79, 2020 | | 2020 |
Data-Driven Modeling and Verification for Artificial Pancreas Systems TS Kushner University of Colorado at Boulder, 2020 | | 2020 |
MULTI-HOUR BLOOD GLUCOSE PREDICTION IN T1D: A PATIENT-SPECIFIC APPROACH USING SHALLOW NEURAL NETWORK MODELS T Kushner, M Breton, S Sankaranarayanan DIABETES TECHNOLOGY & THERAPEUTICS 21, A81-A82, 2019 | | 2019 |
ROBUST DATA-DRIVEN CONTROL OF ARTIFICIAL PANCREAS SYSTEMS USING NEURAL NETWORKS T Kushner, S Dutta, S Sankaranarayanan DIABETES TECHNOLOGY & THERAPEUTICS 21, A83-A84, 2019 | | 2019 |
MBW: Estimation of HIV/AIDS parameters MB Wiki, D Bortz, A Clauset, V Dukic, S Flaxman, M Lladser, B Melbourne, ... | | |
MBW: Modelling the dynamics of a complex life-cycle parasite MB Wiki, D Bortz, A Clauset, V Dukic, S Flaxman, Z Kilpatrick, M Lladser, ... | | |