| The OhioT1DM dataset for blood glucose level prediction: Update 2020 C Marling, R Bunescu CEUR workshop proceedings 2675, 71, 2020 | 352 | 2020 |
| Case-based reasoning in the health sciences: What's next? I Bichindaritz, C Marling Artificial intelligence in medicine 36 (2), 127-135, 2006 | 278 | 2006 |
| A Machine Learning Approach to Predicting Blood Glucose Levels for Diabetes Management. K Plis, RC Bunescu, C Marling, J Shubrook, F Schwartz AAAI Workshop: Modern Artificial Intelligence for Health Analytics, 35-39, 2014 | 207 | 2014 |
| Hypoglycemia in type 2 diabetes-more common than you think: a continuous glucose monitoring study RR Gehlaut, GY Dogbey, FL Schwartz, CR Marling, JH Shubrook Journal of diabetes science and technology 9 (5), 999-1005, 2015 | 155 | 2015 |
| Blood glucose level prediction using physiological models and support vector regression R Bunescu, N Struble, C Marling, J Shubrook, F Schwartz 2013 12th International Conference on Machine Learning and Applications 1 …, 2013 | 139 | 2013 |
| Case-based reasoning in the care of Alzheimer’s disease patients C Marling, P Whitehouse Case-Based Reasoning Research and Development: 4th International Conference …, 2001 | 134 | 2001 |
| Case-based reasoning integrations C Marling, M Sqalli, E Rissland, H Muñoz-Avila, D Aha AI magazine 23 (1), 69-69, 2002 | 110 | 2002 |
| Using LSTMs to learn physiological models of blood glucose behavior S Mirshekarian, R Bunescu, C Marling, F Schwartz 2017 39th Annual international conference of the IEEE engineering in …, 2017 | 104 | 2017 |
| Integrating case‐based and rule‐based reasoning to meet multiple design constraints CR Marling, GJ Petot, LS Sterling Computational intelligence 15 (3), 308-332, 1999 | 103 | 1999 |
| Characterizing blood glucose variability using new metrics with continuous glucose monitoring data. CR Marling, JH Shubrook, SJ Vernier, MT Wiley, FL Schwartz Journal of diabetes science and technology 5 (4), 871, 2011 | 90 | 2011 |
| LSTMs and neural attention models for blood glucose prediction: Comparative experiments on real and synthetic data S Mirshekarian, H Shen, R Bunescu, C Marling 2019 41st annual international conference of the IEEE engineering in …, 2019 | 77 | 2019 |
| An artificial intelligence system for computer-assisted menu planning GJ Petot, C Marling, L Sterling Journal of the American Dietetic Association 98 (9), 1009-1014, 1998 | 75 | 1998 |
| Case-based decision support for patients with type 1 diabetes on insulin pump therapy C Marling, J Shubrook, F Schwartz Advances in Case-Based Reasoning: 9th European Conference, ECCBR 2008, Trier …, 2008 | 73 | 2008 |
| Synergistic case-based reasoning in medical domains C Marling, S Montani, I Bichindaritz, P Funk Expert systems with applications 41 (2), 249-259, 2014 | 55 | 2014 |
| Integrations with case-based reasoning C Marling, E Rissland, A Aamodt The knowledge engineering review 20 (3), 241-245, 2005 | 54 | 2005 |
| Case-based reasoning for planning and world modeling in the robocup small size league C Marling, M Tomko, M Gillen, D Alexander, D Chelberg IJCAI Workshop on issues in designing physical agents for dynamic real-time …, 2003 | 51 | 2003 |
| Toward case-based reasoning for diabetes management: A preliminary clinical study and decision support system prototype C Marling, J Shubrook, F Schwartz Computational intelligence 25 (3), 165-179, 2009 | 49 | 2009 |
| Emerging Applications for Intelligent Diabetes Management C Marling, M Wiley, R Bunescu, J Shubrook, F Schwartz AI Magazine 33 (2), 67-78, 2012 | 41 | 2012 |
| Use of case-based reasoning to enhance intensive management of patients on insulin pump therapy FL Schwartz, JH Shubrook, CR Marling Journal of Diabetes Science and Technology 2 (4), 603-611, 2008 | 37 | 2008 |
| Prescribing exercise regimens for cardiac and pulmonary disease patients with CBR K Evans-Romaine, C Marling Workshop on CBR in the health sciences at 5th international conference on …, 2003 | 36 | 2003 |
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