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Matthew E. Levine
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2020 – today
- 2024
- [j13]Jinlong Wu
, Matthew E. Levine, Tapio Schneider, Andrew M. Stuart:
Learning about structural errors in models of complex dynamical systems. J. Comput. Phys. 513: 113157 (2024) - [c15]Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox:
Hybrid2 Neural ODE Causal Modeling and an Application to Glycemic Response. ICML 2024 - [i5]Jinlong Wu, Matthew E. Levine, Tapio Schneider, Andrew M. Stuart:
Learning About Structural Errors in Models of Complex Dynamical Systems. CoRR abs/2401.00035 (2024) - [i4]Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox:
Hybrid Square Neural ODE Causal Modeling. CoRR abs/2402.17233 (2024) - [i3]Edoardo Calvello, Nikola B. Kovachki, Matthew E. Levine, Andrew M. Stuart:
Continuum Attention for Neural Operators. CoRR abs/2406.06486 (2024) - 2023
- [j12]Marissa Burgermaster, Pooja M. Desai, Elizabeth M. Heitkemper
Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity. J. Biomed. Informatics 144: 104419 (2023) - [j11]David J. Albers
Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data. J. Biomed. Informatics 145: 104477 (2023) - [i2]Ke Alexander Wang, Matthew E. Levine, Jiaxin Shi, Emily B. Fox:
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates. CoRR abs/2304.14300 (2023) - 2021
- [j10]Peter D. Sottile, David J. Albers, Peter E. Dewitt
Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study. J. Am. Medical Informatics Assoc. 28(11): 2354-2365 (2021) - [j9]Elliot G. Mitchell, Esteban G. Tabak, Matthew E. Levine, Lena Mamykina
Enabling personalized decision support with patient-generated data and attributable components. J. Biomed. Informatics 113: 103639 (2021) - [j8]David J. Albers, Matthew E. Levine, Bruce J. Gluckman
Correction: Personalized glucose forecasting for type 2 diabetes using data assimilation. PLoS Comput. Biol. 17(8) (2021) - [c14]Lena Mamykina, Arlene M. Smaldone, Suzanne R. Bakken, Noemie Elhadad, Elliot G. Mitchell, Pooja M. Desai, Matthew E. Levine, Jonathan N. Tobin
Scaling Up HCI Research: from Clinical Trials to Deployment in the Wild. CHI Extended Abstracts 2021: 50:1-50:6 - [c13]Elliot G. Mitchell, Elizabeth M. Heitkemper, Marissa Burgermaster, Matthew E. Levine, Yishen Miao
From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations. CHI 2021: 206:1-206:17 - [i1]Matthew E. Levine, Andrew M. Stuart:
A Framework for Machine Learning of Model Error in Dynamical Systems. CoRR abs/2107.06658 (2021) - 2020
- [j7]Marissa Burgermaster, Jung Hoon Son, Patricia G. Davidson, Arlene M. Smaldone, Gilad Kuperman, Daniel J. Feller, Katherine Gardner Burt, Matthew E. Levine, David J. Albers, Chunhua Weng, Lena Mamykina:
A new approach to integrating patient-generated data with expert knowledge for personalized goal setting: A pilot study. Int. J. Medical Informatics 139: 104158 (2020) - [c12]David J. Albers, Melike Sirlanci Tuysuzoglu, Matthew E. Levine, Caroline Der Nigoghossian, Andrew M. Stuart, Jan Claassen, Bruce J. Gluckman, George Hripcsak:
Lessons learned from assimilating knowledge into machine learning to forecast and control glucose in a critical care setting. AMIA 2020
2010 – 2019
- 2019
- [c11]Elliot G. Mitchell, Marissa Burgermaster, Elizabeth M. Heitkemper, Matthew E. Levine, Yishen Miao, Esteban G. Tabak, Arlene M. Smaldone, David J. Albers, Lena Mamykina:
Feasibility of a machine learning based method to generate personalized nutrition goals for diabetes self-management. AMIA 2019 - [c10]Elliot G. Mitchell, Lena Mamykina, Matthew E. Levine, Esteban G. Tabak, David J. Albers:
Machine learning for personalized decision support with patient-generated health data. AMIA 2019 - [c9]Pooja M. Desai, Elliot G. Mitchell, Maria L. Hwang, Matthew E. Levine, David J. Albers, Lena Mamykina:
Personal Health Oracle: Explorations of Personalized Predictions in Diabetes Self-Management. CHI 2019: 370 - 2018
- [j6]Daniel J. Feller
A visual analytics approach for pattern-recognition in patient-generated data. J. Am. Medical Informatics Assoc. 25(10): 1366-1374 (2018) - [j5]David J. Albers, Matthew E. Levine
Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype. J. Am. Medical Informatics Assoc. 25(10): 1392-1401 (2018) - [j4]George Hripcsak, Matthew E. Levine
Effect of vocabulary mapping for conditions on phenotype cohorts. J. Am. Medical Informatics Assoc. 25(12): 1618-1625 (2018) - [j3]Matthew E. Levine
Methodological variations in lagged regression for detecting physiologic drug effects in EHR data. J. Biomed. Informatics 86: 149-159 (2018) - [c8]David J. Albers, Matthew E. Levine, Andrew M. Stuart, Jan Claassen, Bruce J. Gluckman, George Hripcsak:
Using mechanistic machine learning to forecast glucose and infer physiologic phenotypes in the ICU: what is possible and what are the challenges. AMIA 2018 - [c7]Elliot G. Mitchell, Marissa Burgermaster, Elizabeth M. Heitkemper, Meghan J. Reading, Matthew E. Levine, Yishen Miao, Pooja M. Desai, Lena Mamykina:
An Intelligent Voice Assistant for Diabetes Self-Management: T2D2 - Taming Type 2 Diabetes, Together. AMIA 2018 - [c6]Pooja M. Desai, Matthew E. Levine, David J. Albers, Lena Mamykina:
Pictures Worth a Thousand Words: Reflections on Visualizing Personal Blood Glucose Forecasts for Individuals with Type 2 Diabetes. CHI 2018: 538 - 2017
- [j2]David J. Albers, Matthew E. Levine
Personalized glucose forecasting for type 2 diabetes using data assimilation. PLoS Comput. Biol. 13(4) (2017) - [c5]David J. Albers, Matthew E. Levine, Andrew M. Stuart, Bruce J. Gluckman, George Hripcsak:
Why predicting postprandial glucose using self-monitoring data is difficult. AMIA 2017 - [c4]Elliot G. Mitchell, Matthew E. Levine, David J. Albers, Lena Mamykina:
Reflecting on Diabetes Self-Management Logs with Simulated, Continuous Blood Glucose Curves: A Pilot Study. AMIA 2017 - 2016
- [j1]Lena Mamykina, Matthew E. Levine, Patricia G. Davidson, Arlene M. Smaldone, Noémie Elhadad, David J. Albers:
Data-driven health management: reasoning about personally generated data in diabetes with information technologies. J. Am. Medical Informatics Assoc. 23(3): 526-531 (2016) - [c3]David J. Albers, Matthew E. Levine, Andrew M. Stuart, George Hripcsak, Lena Mamykina:
Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes. AMIA 2016 - [c2]Matthew E. Levine, David J. Albers, George Hripcsak:
Comparing Lagged Linear Correlation, Lagged Regression, Granger Causality, and Vector Autoregression for Uncovering Associations in EHR Data. AMIA 2016 - 2015
- [c1]David J. Albers, Matthew E. Levine, Bruce J. Gluckman, George Hripcsak, Lena Mamykina:
Personalized medicine beyond genetics: using personalized model-based forecasting to help type 2 diabetics understand and predict their post-meal glucose. AMIA 2015
Coauthor Index
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