| 2025 | CHI | Something Similar: Exploring the Usefulness of an On-the-Spot Meal Recommendation System for Health Goal Attainment. | Pooja M. Desai, Ayush Raj, David J. Albers, Aparajita Kashyap, Lena Mamykina |
| 2025 | CHI | T2 Coach: A Qualitative Study of an Automated Health Coach for Diabetes Self-Management. | Elliot G. Mitchell, Pooja M. Desai, Arlene M. Smaldone, Andrea Cassells, Jonathan N. Tobin, David J. Albers, Matthew E. Levine, Lena Mamykina |
| 2022 | AMIA | Optimizing Strategies of Pressure Reactivity Index and Optimal Cerebral Perfusion Pressure Identification for Cerebral Autoregulatory-Guided Clinical Decision Support. | Jennifer K. Briggs, J. N. Stroh, Tellen D. Bennett, Soojin Park, David J. Albers, Brandon Foreman |
| 2022 | AMIA | Informatics Research and Implementation During COVID: Challenges, Opportunities and Recommendations for Building a Sustainable Infrastructure. | Patricia C. Dykes, Sarah Collins Rossetti, Patricia Sengstack, Guilherme Del Fiol, David J. Albers |
| 2022 | AMIA | Using Data Assimilation to Predict Post-Operative Bariatric Surgery Glycemic Status in Adolescents. | Lauren R. Richter, Benjamin Albert, Linying Zhang, Ilene Fennoy, David J. Albers, George Hripcsak |
| 2022 | AMIA | Gaining Purchase on Ventilator-Induced Lung Injury: A Interpretable Approach to Describing Complex System Data via Informed Modeling. | J. N. Stroh, Bradford J. Smith, Peter D. Sottile, George Hripcsak, David J. Albers |
| 2022 | AMIA | A methodology of phenotyping ICU patients: high-fidelity, personalized, and interpretable phenotypes estimation. | Yanran Wang, J. N. Stroh, George Hripcsak, Cecilia C. Low Wang, Julia Wrobel, Caroline Der Nigoghossian, Tellen D. Bennett, David J. Albers |
| 2021 | AMIA | Toward phenotyping of ventilator-induced lung injury with a damage-informed pulmonary model of lung-ventilator interaction. | David J. Albers, Deepak K. Agrawal, Bradford J. Smith, Peter D. Sottile, Tellen D. Bennett, Jake Stroh, George Hripcsak |
| 2021 | CHI | Scaling Up HCI Research: from Clinical Trials to Deployment in the Wild. | 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 |
| 2021 | CHI | From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations. | 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 |
| 2020 | AMIA | Lessons learned from assimilating knowledge into machine learning to forecast and control glucose in a critical care setting. | David J. Albers, Melike Sirlanci Tuysuzoglu, Matthew E. Levine, Caroline Der Nigoghossian, Andrew M. Stuart, Jan Claassen, Bruce J. Gluckman, George Hripcsak |
| 2020 | AMIA | Utilizing Timestamps of Longitudinal Data from Electronic Health Record to Predict Clinical Deterioration Events. | Li-heng Fu, Christopher Knaplund, Kenrick Cato, David J. Albers, Sarah Collins Rossetti |
| 2019 | AMIA | Feasibility of a machine learning based method to generate personalized nutrition goals for diabetes self-management. | 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 | AMIA | Machine learning for personalized decision support with patient-generated health data. | Elliot G. Mitchell, Lena Mamykina, Matthew E. Levine, Esteban G. Tabak, David J. Albers |
| 2019 | AMIA | Leveraging Clinical Expertise as a Feature - not an Outcome - of Predictive Models: Evaluation of an Early Warning System Use Case. | Sarah Collins Rossetti, Christopher Knaplund, David J. Albers, Abdul A. Tariq, Kui Tang, David K. Vawdrey, Natalie Yip, Patricia C. Dykes, Jeffrey G. Klann, Min-Jeoung Kang, Jose P. Garcia, Li-heng Fu, Kumiko O. Schnock, Kenrick Cato |
| 2019 | CHI | Personal Health Oracle: Explorations of Personalized Predictions in Diabetes Self-Management. | Pooja M. Desai, Elliot G. Mitchell, Maria L. Hwang, Matthew E. Levine, David J. Albers, Lena Mamykina |
| 2018 | AMIA | Using mechanistic machine learning to forecast glucose and infer physiologic phenotypes in the ICU: what is possible and what are the challenges. | David J. Albers, Matthew E. Levine, Andrew M. Stuart, Jan Claassen, Bruce J. Gluckman, George Hripcsak |
| 2018 | CHI | Pictures Worth a Thousand Words: Reflections on Visualizing Personal Blood Glucose Forecasts for Individuals with Type 2 Diabetes. | Pooja M. Desai, Matthew E. Levine, David J. Albers, Lena Mamykina |
| 2017 | AMIA | Why predicting postprandial glucose using self-monitoring data is difficult. | David J. Albers, Matthew E. Levine, Andrew M. Stuart, Bruce J. Gluckman, George Hripcsak |
| 2017 | AMIA | Reflecting on Diabetes Self-Management Logs with Simulated, Continuous Blood Glucose Curves: A Pilot Study. | Elliot G. Mitchell, Matthew E. Levine, David J. Albers, Lena Mamykina |
| 2016 | AMIA | Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes. | David J. Albers, Matthew E. Levine, Andrew M. Stuart, George Hripcsak, Lena Mamykina |
| 2016 | AMIA | Approaches for using temporal and other filters for next generation phenotype discovery. | David J. Albers, Adler J. Perotte, George Hripcsak |
| 2016 | AMIA | Comparing Lagged Linear Correlation, Lagged Regression, Granger Causality, and Vector Autoregression for Uncovering Associations in EHR Data. | Matthew E. Levine, David J. Albers, George Hripcsak |
| 2015 | AMIA | Personalized medicine beyond genetics: using personalized model-based forecasting to help type 2 diabetics understand and predict their post-meal glucose. | David J. Albers, Matthew E. Levine, Bruce J. Gluckman, George Hripcsak, Lena Mamykina |
| 2015 | AMIA | Model Selection For EHR Laboratory Tests Preserving Healthcare Context and Underlying Physiology. | David J. Albers, Rimma Pivovarov, J. Michael Schmidt, Noemie Elhadad, George Hripcsak |
| 2014 | AMIA | Model selection for EHR laboratory variables: how physiology and the health care process can influence EHR laboratory data and their model representations. | David J. Albers, Rimma Pivovarov, Noemie Elhadad, George Hripcsak |
| 2013 | AMIA | Using patient laboratory measurement values and dynamics to deconvolve EHR bias and define acuity-based phenotypes. | David J. Albers, Rimma Pivovarov, George Hripcsak, Noemie Elhadad |
| 2012 | AMIA | Using Empirical orthogonal functions to identify temporally important variables to understand time-dependent pathophysiologic and phenotypic differences in patients. | David J. Albers, Jan Claassen, George Hripcsak |