Matthew E. Levine

37 papers A* 5Misc 10Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Canonical Bayesian Linear System Identification. CoRR Andrey Bryutkin, Matthew E. Levine, Iñigo Urteaga, Youssef Marzouk
2025	J	`jnl`	Continuum Attention for Neural Operators. J. Mach. Learn. Res. Edoardo Calvello, Nikola B. Kovachki, Matthew E. Levine, Andrew M. Stuart
2025	A*	`conf`	T2 Coach: A Qualitative Study of an Automated Health Coach for Diabetes Self-Management. CHI Elliot G. Mitchell, Pooja M. Desai, Arlene M. Smaldone, Andrea Cassells, Jonathan N. Tobin, David J. Albers, Matthew E. Levine, Lena Mamykina
2024	J	`jnl`	Continuum Attention for Neural Operators. CoRR Edoardo Calvello, Nikola B. Kovachki, Matthew E. Levine, Andrew M. Stuart
2024	J	`jnl`	Hybrid Square Neural ODE Causal Modeling. CoRR Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox
2024	A*	`conf`	Hybrid2 Neural ODE Causal Modeling and an Application to Glycemic Response. ICML Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox
2024	J	`jnl`	Learning About Structural Errors in Models of Complex Dynamical Systems. CoRR Jinlong Wu, Matthew E. Levine, Tapio Schneider, Andrew M. Stuart
2024	J	`jnl`	Learning about structural errors in models of complex dynamical systems. J. Comput. Phys. Jinlong Wu, Matthew E. Levine, Tapio Schneider, Andrew M. Stuart
2023	J	`jnl`	Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data. J. Biomed. Informatics David J. Albers, Melike Sirlanci, Matthew E. Levine, Jan Claassen, Caroline Der Nigoghossian, George Hripcsak
2023	J	`jnl`	Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates. CoRR Ke Alexander Wang, Matthew E. Levine, Jiaxin Shi, Emily B. Fox
2023	—	`—`	Machine Learning and Data Assimilation for Blending Incomplete Models and Noisy Data. Matthew E. Levine
2023	J	`jnl`	Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity. J. Biomed. Informatics Marissa Burgermaster, Pooja M. Desai, Elizabeth M. Heitkemper, Filippa Juul, Elliot G. Mitchell, Meghan Reading Turchioe, David J. Albers, Matthew E. Levine, Dagny Larson, Lena Mamykina
2021	J	`jnl`	A Framework for Machine Learning of Model Error in Dynamical Systems. CoRR Matthew E. Levine, Andrew M. Stuart
2021	J	`jnl`	Correction: Personalized glucose forecasting for type 2 diabetes using data assimilation. PLoS Comput. Biol. David J. Albers, Matthew E. Levine, Bruce J. Gluckman, Henry N. Ginsberg, George Hripcsak, Lena Mamykina
2021	J	`jnl`	Enabling personalized decision support with patient-generated data and attributable components. J. Biomed. Informatics Elliot G. Mitchell, Esteban G. Tabak, Matthew E. Levine, Lena Mamykina, David J. Albers
2021	A*	`conf`	From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations. CHI Elliot G. Mitchell, Elizabeth M. Heitkemper, Marissa Burgermaster, Matthew E. Levine, Yishen Miao, Maria L. Hwang, Pooja M. Desai, Andrea Cassells, Jonathan N. Tobin, Esteban G. Tabak, David J. Albers, Arlene M. Smaldone, Lena Mamykina
2021	J	`jnl`	Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study. J. Am. Medical Informatics Assoc. Peter D. Sottile, David J. Albers, Peter E. Dewitt, Seth Russell, J. N. Stroh, David P. Kao, Bonnie Adrian, Matthew E. Levine, Ryan Mooney, Lenny Larchick, Jean S. Kutner, Matthew K. Wynia, Jeffrey J. Glasheen, Tellen D. Bennett
2021	—	`conf`	Scaling Up HCI Research: from Clinical Trials to Deployment in the Wild. CHI Extended Abstracts Lena Mamykina, Arlene M. Smaldone, Suzanne R. Bakken, Noemie Elhadad, Elliot G. Mitchell, Pooja M. Desai, Matthew E. Levine, Jonathan N. Tobin, Andrea Cassells, Patricia G. Davidson, David J. Albers, George Hripcsak
2020	J	`jnl`	A new approach to integrating patient-generated data with expert knowledge for personalized goal setting: A pilot study. Int. J. Medical Informatics 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
2020	Misc	`conf`	Lessons learned from assimilating knowledge into machine learning to forecast and control glucose in a critical care setting. AMIA David J. Albers, Melike Sirlanci Tuysuzoglu, Matthew E. Levine, Caroline Der Nigoghossian, Andrew M. Stuart, Jan Claassen, Bruce J. Gluckman, George Hripcsak
2019	Misc	`conf`	Feasibility of a machine learning based method to generate personalized nutrition goals for diabetes self-management. AMIA Elliot G. Mitchell, Marissa Burgermaster, Elizabeth M. Heitkemper, Matthew E. Levine, Yishen Miao, Esteban G. Tabak, Arlene M. Smaldone, David J. Albers, Lena Mamykina
2019	Misc	`conf`	Machine learning for personalized decision support with patient-generated health data. AMIA Elliot G. Mitchell, Lena Mamykina, Matthew E. Levine, Esteban G. Tabak, David J. Albers
2019	A*	`conf`	Personal Health Oracle: Explorations of Personalized Predictions in Diabetes Self-Management. CHI Pooja M. Desai, Elliot G. Mitchell, Maria L. Hwang, Matthew E. Levine, David J. Albers, Lena Mamykina
2018	J	`jnl`	A visual analytics approach for pattern-recognition in patient-generated data. J. Am. Medical Informatics Assoc. Daniel J. Feller, Marissa Burgermaster, Matthew E. Levine, Arlene M. Smaldone, Patricia G. Davidson, David J. Albers, Lena Mamykina
2018	Misc	`conf`	An Intelligent Voice Assistant for Diabetes Self-Management: T2D2 - Taming Type 2 Diabetes, Together. AMIA Elliot G. Mitchell, Marissa Burgermaster, Elizabeth M. Heitkemper, Meghan J. Reading, Matthew E. Levine, Yishen Miao, Pooja M. Desai, Lena Mamykina
2018	J	`jnl`	Effect of vocabulary mapping for conditions on phenotype cohorts. J. Am. Medical Informatics Assoc. George Hripcsak, Matthew E. Levine, Ning Shang, Patrick B. Ryan
2018	J	`jnl`	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. David J. Albers, Matthew E. Levine, Andrew M. Stuart, Lena Mamykina, Bruce J. Gluckman, George Hripcsak
2018	J	`jnl`	Methodological variations in lagged regression for detecting physiologic drug effects in EHR data. J. Biomed. Informatics Matthew E. Levine, David J. Albers, George Hripcsak
2018	A*	`conf`	Pictures Worth a Thousand Words: Reflections on Visualizing Personal Blood Glucose Forecasts for Individuals with Type 2 Diabetes. CHI Pooja M. Desai, Matthew E. Levine, David J. Albers, Lena Mamykina
2018	Misc	`conf`	Using mechanistic machine learning to forecast glucose and infer physiologic phenotypes in the ICU: what is possible and what are the challenges. AMIA David J. Albers, Matthew E. Levine, Andrew M. Stuart, Jan Claassen, Bruce J. Gluckman, George Hripcsak
2017	J	`jnl`	Personalized glucose forecasting for type 2 diabetes using data assimilation. PLoS Comput. Biol. David J. Albers, Matthew E. Levine, Bruce J. Gluckman, Henry N. Ginsberg, George Hripcsak, Lena Mamykina
2017	Misc	`conf`	Reflecting on Diabetes Self-Management Logs with Simulated, Continuous Blood Glucose Curves: A Pilot Study. AMIA Elliot G. Mitchell, Matthew E. Levine, David J. Albers, Lena Mamykina
2017	Misc	`conf`	Why predicting postprandial glucose using self-monitoring data is difficult. AMIA David J. Albers, Matthew E. Levine, Andrew M. Stuart, Bruce J. Gluckman, George Hripcsak
2016	Misc	`conf`	Comparing Lagged Linear Correlation, Lagged Regression, Granger Causality, and Vector Autoregression for Uncovering Associations in EHR Data. AMIA Matthew E. Levine, David J. Albers, George Hripcsak
2016	J	`jnl`	Data-driven health management: reasoning about personally generated data in diabetes with information technologies. J. Am. Medical Informatics Assoc. Lena Mamykina, Matthew E. Levine, Patricia G. Davidson, Arlene M. Smaldone, Noémie Elhadad, David J. Albers
2016	Misc	`conf`	Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes. AMIA David J. Albers, Matthew E. Levine, Andrew M. Stuart, George Hripcsak, Lena Mamykina
2015	Misc	`conf`	Personalized medicine beyond genetics: using personalized model-based forecasting to help type 2 diabetics understand and predict their post-meal glucose. AMIA David J. Albers, Matthew E. Levine, Bruce J. Gluckman, George Hripcsak, Lena Mamykina