David J. Albers

67 papers A* 4Misc 22Journal 37Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Interdisciplinary development and application of computational methods in informatics for clinical applications. J. Am. Medical Informatics Assoc. David J. Albers, Kenrick Cato, Anita Layton, Sarah Collins Rossetti
2026	J	`jnl`	Navigating the landscape of personalized oncology: overcoming challenges and expanding horizons with computational modeling. J. Am. Medical Informatics Assoc. Melike Sirlanci, David J. Albers, Jennifer K. Briggs, Clayton Smith, Tellen D. Bennett, Steven M. Bair
2026	J	`jnl`	Predicting intracranial pressure monitor placement in children with traumatic brain injury: a prospective cohort study to develop a clinical decision support tool. J. Am. Medical Informatics Assoc. Seth Russell, Peter E. Dewitt, Laura J. Helmkamp, Kathryn Colborn, Charlotte Gray, Margaret Rebull, Yamila L. Sierra, Rachel Greer, Lexi Petruccelli, Sara Shankman, Todd C. Hankinson, Fuyong Xing, David J. Albers, Tellen D. Bennett
2025	J	`jnl`	Equipping mathematical models for hospital dynamics using information theory. npj Digit. Medicine Jeremy A. Balch, Jackson G. Brandberg, Robert T. Andris, Ian G. Mesner, Daniel Nametz, Murad Megjhani, Matthew M. Ruppert, Die Hu, Matthew T. Clark, Benjamin Shickel, Benjamin L. Ranard, John B. Delos, David J. Albers, Tyler J. Loftus, Soojin Park, J. Randall Moorman
2025	J	`jnl`	Navigating the consequences of mechanical ventilation in clinical intensive care settings through an evolutionary game-theoretic framework. CoRR David J. Albers, Tellen D. Bennett, Jana de Wiljes, Bradford J. Smith, Peter D. Sottile, J. N. Stroh
2025	J	`jnl`	Personalizing the Pressure Reactivity Index for Quantifying Cerebral Autoregulation in Neurocritical Care. IEEE Trans. Biomed. Eng. Jennifer K. Briggs, J. N. Stroh, Brandon Foreman, Soojin Park, Tellen D. Bennett, David J. Albers
2025	—	`conf`	Something Similar: Exploring the Usefulness of an On-the-Spot Meal Recommendation System for Health Goal Attainment. CHI Extended Abstracts Pooja M. Desai, Ayush Raj, David J. Albers, Aparajita Kashyap, Lena Mamykina
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`	Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model. Comput. Biol. Medicine Deepak K. Agrawal, Bradford J. Smith, Peter D. Sottile, George Hripcsak, David J. Albers
2023	J	`jnl`	A methodology of phenotyping ICU patients from EHR data: High-fidelity, personalized, and interpretable phenotypes estimation. J. Biomed. Informatics Yanran Wang, J. N. Stroh, George Hripcsak, Cecilia C. Low Wang, Tellen D. Bennett, Julia Wrobel, Caroline Der Nigoghossian, Scott W. Mueller, Jan Claassen, David J. Albers
2023	J	`jnl`	Hypothesis-driven modeling of the human lung-ventilator system: A characterization tool for Acute Respiratory Distress Syndrome research. J. Biomed. Informatics J. N. Stroh, Bradford J. Smith, Peter D. Sottile, George Hripcsak, David J. Albers
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`	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
2022	Misc	`conf`	A methodology of phenotyping ICU patients: high-fidelity, personalized, and interpretable phenotypes estimation. AMIA Yanran Wang, J. N. Stroh, George Hripcsak, Cecilia C. Low Wang, Julia Wrobel, Caroline Der Nigoghossian, Tellen D. Bennett, David J. Albers
2022	Misc	`conf`	Gaining Purchase on Ventilator-Induced Lung Injury: A Interpretable Approach to Describing Complex System Data via Informed Modeling. AMIA J. N. Stroh, Bradford J. Smith, Peter D. Sottile, George Hripcsak, David J. Albers
2022	Misc	`conf`	Informatics Research and Implementation During COVID: Challenges, Opportunities and Recommendations for Building a Sustainable Infrastructure. AMIA Patricia C. Dykes, Sarah Collins Rossetti, Patricia Sengstack, Guilherme Del Fiol, David J. Albers
2022	Misc	`conf`	Optimizing Strategies of Pressure Reactivity Index and Optimal Cerebral Perfusion Pressure Identification for Cerebral Autoregulatory-Guided Clinical Decision Support. AMIA Jennifer K. Briggs, J. N. Stroh, Tellen D. Bennett, Soojin Park, David J. Albers, Brandon Foreman
2022	Misc	`conf`	Using Data Assimilation to Predict Post-Operative Bariatric Surgery Glycemic Status in Adolescents. AMIA Lauren R. Richter, Benjamin Albert, Linying Zhang, Ilene Fennoy, David J. Albers, George Hripcsak
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`	Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework. J. Am. Medical Informatics Assoc. Sarah Collins Rossetti, Chris Knaplund, David J. Albers, Patricia C. Dykes, Min-Jeoung Kang, Zfania Tom Korach, Li Zhou, Kumiko Schnock, Jose P. Garcia, Jessica M. Schwartz, Li-heng Fu, Jeffrey G. Klann, Graham Lowenthal, Kenrick Cato
2021	J	`jnl`	Identifying nursing documentation patterns associated with patient deterioration and recovery from deterioration in critical and acute care settings. Int. J. Medical Informatics Kumiko O. Schnock, Min-Jeoung Kang, Sarah Collins Rossetti, Jose P. Garcia, Graham Lowenthal, Chris Knaplund, Frank Y. Chang, David J. Albers, Zfania Tom Korach, Li Zhou, Jeffrey G. Klann, Kenrick Cato, David W. Bates, Patricia C. Dykes
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
2021	Misc	`conf`	Toward phenotyping of ventilator-induced lung injury with a damage-informed pulmonary model of lung-ventilator interaction. AMIA David J. Albers, Deepak K. Agrawal, Bradford J. Smith, Peter D. Sottile, Tellen D. Bennett, Jake Stroh, George Hripcsak
2021	J	`jnl`	Utilizing timestamps of longitudinal electronic health record data to classify clinical deterioration events. J. Am. Medical Informatics Assoc. Li-heng Fu, Chris Knaplund, Kenrick Cato, Adler J. Perotte, Min-Jeoung Kang, Patricia C. Dykes, David J. Albers, Sarah Collins Rossetti
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	J	`jnl`	Development and validation of early warning score system: A systematic literature review. J. Biomed. Informatics Li-heng Fu, Jessica M. Schwartz, Amanda J. Moy, Christopher Knaplund, Min-Jeoung Kang, Kumiko O. Schnock, Jose P. Garcia, Haomiao Jia, Patricia C. Dykes, Kenrick Cato, David J. Albers, Sarah Collins Rossetti
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
2020	Misc	`conf`	Utilizing Timestamps of Longitudinal Data from Electronic Health Record to Predict Clinical Deterioration Events. AMIA Li-heng Fu, Christopher Knaplund, Kenrick Cato, David J. Albers, Sarah Collins Rossetti
2019	J	`jnl`	Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. Artif. Intell. Medicine Ashenafi Zebene Woldaregay, Eirik Årsand, Ståle Walderhaug, David J. Albers, Lena Mamykina, Taxiarchis Botsis, Gunnar Hartvigsen
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`	Leveraging Clinical Expertise as a Feature - not an Outcome - of Predictive Models: Evaluation of an Early Warning System Use Case. AMIA 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	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	—	`conf`	Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics. MLHC Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy, David J. Albers, Noémie Elhadad
2019	J	`jnl`	Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics. CoRR Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy, David J. Albers, Noémie Elhadad
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	J	`jnl`	Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms. J. Biomed. Informatics David J. Albers, Noémie Elhadad, Jan Claassen, Rimma Perotte, Andrew Goldstein, George Hripcsak
2018	J	`jnl`	High-fidelity phenotyping: richness and freedom from bias. J. Am. Medical Informatics Assoc. George Hripcsak, David J. Albers
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`	An Interoperable Similarity-based Cohort Identification Method Using the OMOP Common Data Model Version 5.0. J. Heal. Informatics Res. Shreya Chakrabarti, Anando Sen, Vojtech Huser, Gregory William Hruby, Alexander Rusanov, David J. Albers, Chunhua Weng
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	J	`jnl`	Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes. CoRR Iñigo Urteaga, David J. Albers, Marija Vlajic Wheeler, Anna Druet, Hans Raffauf, Noémie Elhadad
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`	Approaches for using temporal and other filters for next generation phenotype discovery. AMIA David J. Albers, Adler J. Perotte, 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`	Model Selection For EHR Laboratory Tests Preserving Healthcare Context and Underlying Physiology. AMIA David J. Albers, Rimma Pivovarov, J. Michael Schmidt, Noemie Elhadad, George Hripcsak
2015	J	`jnl`	Parameterizing time in electronic health record studies. J. Am. Medical Informatics Assoc. George Hripcsak, David J. Albers, Adler J. Perotte
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
2014	J	`jnl`	Identifying and mitigating biases in EHR laboratory tests. J. Biomed. Informatics Rimma Pivovarov, David J. Albers, Jorge L. Sepulveda, Noémie Elhadad
2014	Misc	`conf`	Model selection for EHR laboratory variables: how physiology and the health care process can influence EHR laboratory data and their model representations. AMIA David J. Albers, Rimma Pivovarov, Noemie Elhadad, George Hripcsak
2014	J	`jnl`	Survival analysis with electronic health record data: Experiments with chronic kidney disease. Stat. Anal. Data Min. Yolanda Hagar, David J. Albers, Rimma Pivovarov, Herbert S. Chase, Vanja Dukic, Noémie Elhadad
2014	J	`jnl`	Temporal trends of hemoglobin A1c testing. J. Am. Medical Informatics Assoc. Rimma Pivovarov, David J. Albers, George Hripcsak, Jorge L. Sepulveda, Noémie Elhadad
2013	J	`jnl`	Next-generation phenotyping of electronic health records. J. Am. Medical Informatics Assoc. George Hripcsak, David J. Albers
2013	Misc	`conf`	Using patient laboratory measurement values and dynamics to deconvolve EHR bias and define acuity-based phenotypes. AMIA David J. Albers, Rimma Pivovarov, George Hripcsak, Noemie Elhadad
2012	—	`conf`	Data assimilation of glucose dynamics for use in the intensive care unit. EMBC Madineh Sedigh-Sarvestani, David J. Albers, Bruce J. Gluckman
2012	Misc	`conf`	Using Empirical orthogonal functions to identify temporally important variables to understand time-dependent pathophysiologic and phenotypic differences in patients. AMIA David J. Albers, Jan Claassen, George Hripcsak
2011	J	`jnl`	Exploiting time in electronic health record correlations. J. Am. Medical Informatics Assoc. George Hripcsak, David J. Albers, Adler J. Perotte
2011	J	`jnl`	Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations CoRR David J. Albers, George Hripcsak