David J. Albers

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 45

Top Topics

Gaussian Process

Decision Support

Data Assimilation

Top Venues

J. Am. Medical Informatics Assoc.

J. Biomed. Informatics

Publications

Deepak K. Agrawal, Bradford J. Smith, Peter D. Sottile, George Hripcsak, David J. Albers
Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model. Comput. Biol. Medicine 173 (2024)
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
Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity. J. Biomed. Informatics 144 (2023)
David J. Albers, Melike Sirlanci, Matthew E. Levine, Jan Claassen, Caroline Der Nigoghossian, George Hripcsak
Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data. J. Biomed. Informatics 145 (2023)
J. N. Stroh, Bradford J. Smith, Peter D. Sottile, George Hripcsak, David J. Albers
Hypothesis-driven modeling of the human lung-ventilator system: A characterization tool for Acute Respiratory Distress Syndrome research. J. Biomed. Informatics 137 (2023)
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
A methodology of phenotyping ICU patients from EHR data: High-fidelity, personalized, and interpretable phenotypes estimation. J. Biomed. Informatics 148 (2023)
Jennifer K. Briggs, J. N. Stroh, Tellen Bennett, Soojin Park, David J. Albers, Brandon Foreman
Optimizing Strategies of Pressure Reactivity Index and Optimal Cerebral Perfusion Pressure Identification for Cerebral Autoregulatory-Guided Clinical Decision Support. AMIA (2022)
Patricia C. Dykes, Sarah Collins Rossetti, Patricia Sengstack, Guilherme Del Fiol, David J. Albers
Informatics Research and Implementation During COVID: Challenges, Opportunities and Recommendations for Building a Sustainable Infrastructure. AMIA (2022)
Yanran Wang, J. N. Stroh, George Hripcsak, Cecilia C. Low Wang, Julia Wrobel, Caroline Der Nigoghossian, Tellen D. Bennett, David J. Albers
A methodology of phenotyping ICU patients: high-fidelity, personalized, and interpretable phenotypes estimation. AMIA (2022)
J. N. Stroh, Bradford Smith, Peter D. Sottile, George Hripcsak, David J. Albers
Gaining Purchase on Ventilator-Induced Lung Injury: A Interpretable Approach to Describing Complex System Data via Informed Modeling. AMIA (2022)
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
Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study. J. Am. Medical Informatics Assoc. 28 (11) (2021)
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
Scaling Up HCI Research: from Clinical Trials to Deployment in the Wild. CHI Extended Abstracts (2021)
David J. Albers, Matthew E. Levine, Bruce J. Gluckman, Henry N. Ginsberg, George Hripcsak, Lena Mamykina
Correction: Personalized glucose forecasting for type 2 diabetes using data assimilation. PLoS Comput. Biol. 17 (8) (2021)
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
Identifying nursing documentation patterns associated with patient deterioration and recovery from deterioration in critical and acute care settings. Int. J. Medical Informatics 153 (2021)
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
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. 28 (6) (2021)
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
From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations. CHI (2021)
Elliot G. Mitchell, Esteban G. Tabak, Matthew E. Levine, Lena Mamykina, David J. Albers
Enabling personalized decision support with patient-generated data and attributable components. J. Biomed. Informatics 113 (2021)
Li-heng Fu, Chris Knaplund, Kenrick Cato, Adler J. Perotte, Min-Jeoung Kang, Patricia C. Dykes, David J. Albers, Sarah Collins Rossetti
Utilizing timestamps of longitudinal electronic health record data to classify clinical deterioration events. J. Am. Medical Informatics Assoc. 28 (9) (2021)
David J. Albers, Deepak Agrawal, Bradford Smith, Peter D. Sottile, Tellen D. Bennett, Jake Stroh, George Hripcsak
Toward phenotyping of ventilator-induced lung injury with a damage-informed pulmonary model of lung-ventilator interaction. AMIA (2021)
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 (2020)
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
Development and validation of early warning score system: A systematic literature review. J. Biomed. Informatics 105 (2020)
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)
Li-heng Fu, Christopher Knaplund, Kenrick Cato, David J. Albers, Sarah Collins Rossetti
Utilizing Timestamps of Longitudinal Data from Electronic Health Record to Predict Clinical Deterioration Events. AMIA (2020)
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
Leveraging Clinical Expertise as a Feature - not an Outcome - of Predictive Models: Evaluation of an Early Warning System Use Case. AMIA (2019)
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)
Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy, David J. Albers, Noémie Elhadad
Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics. CoRR (2019)
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)
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)
Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy, David J. Albers, Noémie Elhadad
Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics. MLHC (2019)
Ashenafi Zebene Woldaregay, Eirik Årsand, Ståle Walderhaug, David J. Albers, Lena Mamykina, Taxiarchis Botsis, Gunnar Hartvigsen
Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. Artif. Intell. Medicine 98 (2019)
Matthew E. Levine, David J. Albers, George Hripcsak
Methodological variations in lagged regression for detecting physiologic drug effects in EHR data. J. Biomed. Informatics 86 (2018)
David J. Albers, Noémie Elhadad, Jan Claassen, Rimma Perotte, A. Goldstein, George Hripcsak
Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms. J. Biomed. Informatics 78 (2018)
David J. Albers, Matthew E. Levine, Andrew M. Stuart, Lena Mamykina, Bruce J. Gluckman, George Hripcsak
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) (2018)
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)
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)
Daniel J. Feller, Marissa Burgermaster, Matthew E. Levine, Arlene M. Smaldone, Patricia G. Davidson, David J. Albers, Lena Mamykina
A visual analytics approach for pattern-recognition in patient-generated data. J. Am. Medical Informatics Assoc. 25 (10) (2018)
George Hripcsak, David J. Albers
High-fidelity phenotyping: richness and freedom from bias. J. Am. Medical Informatics Assoc. 25 (3) (2018)
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)
Shreya Chakrabarti, Anando Sen, Vojtech Huser, Gregory William Hruby, Alexander Rusanov, David J. Albers, Chunhua Weng
An Interoperable Similarity-based Cohort Identification Method Using the OMOP Common Data Model Version 5.0. J. Heal. Informatics Res. 1 (1) (2017)
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)
Iñigo Urteaga, David J. Albers, Marija Vlajic Wheeler, Anna Druet, Hans Raffauf, Noémie Elhadad
Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes. CoRR (2017)
David J. Albers, Matthew E. Levine, Bruce J. Gluckman, Henry N. Ginsberg, George Hripcsak, Lena Mamykina
Personalized glucose forecasting for type 2 diabetes using data assimilation. PLoS Comput. Biol. 13 (4) (2017)
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)
David J. Albers, Adler J. Perotte, George Hripcsak
Approaches for using temporal and other filters for next generation phenotype discovery. AMIA (2016)
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) (2016)
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)
George Hripcsak, David J. Albers, Adler J. Perotte
Parameterizing time in electronic health record studies. J. Am. Medical Informatics Assoc. 22 (4) (2015)
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)
David J. Albers, Rimma Pivovarov, J. Michael Schmidt, Noemie Elhadad, George Hripcsak
Model Selection For EHR Laboratory Tests Preserving Healthcare Context and Underlying Physiology. AMIA (2015)
Yolanda Hagar, David J. Albers, Rimma Pivovarov, Herbert S. Chase, Vanja Dukic, Noémie Elhadad
Survival analysis with electronic health record data: Experiments with chronic kidney disease. Stat. Anal. Data Min. 7 (5) (2014)
Rimma Pivovarov, David J. Albers, George Hripcsak, Jorge L. Sepulveda, Noémie Elhadad
Temporal trends of hemoglobin A1c testing. J. Am. Medical Informatics Assoc. 21 (6) (2014)
Rimma Pivovarov, David J. Albers, Jorge L. Sepulveda, Noémie Elhadad
Identifying and mitigating biases in EHR laboratory tests. J. Biomed. Informatics 51 (2014)
David J. Albers, Rimma Pivovarov, Noemie Elhadad, George Hripcsak
Model selection for EHR laboratory variables: how physiology and the health care process can influence EHR laboratory data and their model representations. AMIA (2014)
David J. Albers, Rimma Pivovarov, George Hripcsak, Noemie Elhadad
Using patient laboratory measurement values and dynamics to deconvolve EHR bias and define acuity-based phenotypes. AMIA (2013)
George Hripcsak, David J. Albers
Next-generation phenotyping of electronic health records. J. Am. Medical Informatics Assoc. 20 (1) (2013)
David J. Albers, Jan Claassen, George Hripcsak
Using Empirical orthogonal functions to identify temporally important variables to understand time-dependent pathophysiologic and phenotypic differences in patients. AMIA (2012)
Madineh Sedigh-Sarvestani, David J. Albers, Bruce J. Gluckman
Data assimilation of glucose dynamics for use in the intensive care unit. EMBC (2012)
David J. Albers, George Hripcsak
Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations CoRR (2011)
George Hripcsak, David J. Albers, Adler J. Perotte
Exploiting time in electronic health record correlations. J. Am. Medical Informatics Assoc. 18 (Supplement) (2011)