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A Machine Learning Approach to Predicting Blood Glucose Levels for Diabetes Management.

, , , , and . AAAI Workshop: Modern Artificial Intelligence for Health Analytics, volume WS-14-08 of AAAI Workshops, AAAI, (2014)

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Using LSTMs to learn physiological models of blood glucose behavior., , , and . EMBC, page 2887-2891. IEEE, (2017)Automatic Detection of Excessive Glycemic Variability for Diabetes Management., , , , and . ICMLA (2), page 148-154. IEEE Computer Society, (2011)978-0-7695-4607-0.A General Neural Architecture for Carbohydrate and Bolus Recommendations in Type 1 Diabetes Management., , and . KDH@ECAI, volume 2675 of CEUR Workshop Proceedings, page 43-47. CEUR-WS.org, (2020)Blood Glucose Level Prediction Using Physiological Models and Support Vector Regression., , , , and . ICMLA (1), page 135-140. IEEE, (2013)The 4 Diabetes Support System: A Case Study in CBR Research and Development., , , , , and . ICCBR, volume 6880 of Lecture Notes in Computer Science, page 137-150. Springer, (2011)Emerging Applications for Intelligent Diabetes Management., , , , and . IAAI, page 1668-1673. AAAI, (2011)Preface for the special section on case-based reasoning in the health sciences., , and . Expert Syst. Appl., 41 (2): 247-248 (2014)From Physician Queries to Logical Forms for Efficient Exploration of Patient Data., , , and . ICSC, page 371-374. IEEE, (2019)CS0 for Computer Science Majors at Ohio University., and . SIGCSE, page 138-143. ACM, (2016)Recent Themes in Case-Based Reasoning and Knowledge Discovery., , and . FLAIRS, page 499-502. AAAI Press, (2017)