Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations - David J. Albers; George Hripcsak (CoRR, 2011)

Exploiting time in electronic health record correlations. - George Hripcsak; David J. Albers; Adler J. Perotte (J. Am. Medical Informatics Assoc., 2011)

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 (AMIA, 2012)

Data assimilation of glucose dynamics for use in the intensive care unit. - Madineh Sedigh-Sarvestani; David J. Albers; Bruce J. Gluckman (EMBC, 2012)

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 (AMIA, 2013)

Next-generation phenotyping of electronic health records. - George Hripcsak; David J. Albers (J. Am. Medical Informatics Assoc., 2013)

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 (AMIA, 2014)

Temporal trends of hemoglobin A1c testing. - Rimma Pivovarov; David J. Albers; George Hripcsak; Jorge L. Sepulveda; Noémie Elhadad (J. Am. Medical Informatics Assoc., 2014)

Identifying and mitigating biases in EHR laboratory tests. - Rimma Pivovarov; David J. Albers; Jorge L. Sepulveda; Noémie Elhadad (J. Biomed. Informatics, 2014)

Survival analysis with electronic health record data: Experiments with chronic kidney disease. - Yolanda Hagar; David J. Albers; Rimma Pivovarov; Herbert S. Chase; Vanja Dukic; Noémie Elhadad (Stat. Anal. Data Min., 2014)

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 (AMIA, 2015)

Model Selection For EHR Laboratory Tests Preserving Healthcare Context and Underlying Physiology. - David J. Albers; Rimma Pivovarov; J. Michael Schmidt; Noemie Elhadad; George Hripcsak (AMIA, 2015)

Parameterizing time in electronic health record studies. - George Hripcsak; David J. Albers; Adler J. Perotte (J. Am. Medical Informatics Assoc., 2015)

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 (AMIA, 2016)

Approaches for using temporal and other filters for next generation phenotype discovery. - David J. Albers; Adler J. Perotte; George Hripcsak (AMIA, 2016)

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 (AMIA, 2016)

Data-driven health management: reasoning about personally generated data in diabetes with information technologies. - Lena Mamykina; Matthew E. Levine; Patricia G. Davidson; Arlene M. Smaldone; Noémie Elhadad; David J. Albers (J. Am. Medical Informatics Assoc., 2016)

Why predicting postprandial glucose using self-monitoring data is difficult. - David J. Albers; Matthew E. Levine; Andrew M. Stuart; Bruce J. Gluckman; George Hripcsak (AMIA, 2017)

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 (AMIA, 2017)

Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes. - Iñigo Urteaga; David J. Albers; Marija Vlajic Wheeler; Anna Druet; Hans Raffauf; Noémie Elhadad (CoRR, 2017)

An Interoperable Similarity-based Cohort Identification Method Using the OMOP Common Data Model Version 5.0. - Shreya Chakrabarti; Anando Sen; Vojtech Huser; Gregory William Hruby; Alexander Rusanov; David J. Albers; Chunhua Weng (J. Heal. Informatics Res., 2017)

Personalized glucose forecasting for type 2 diabetes using data assimilation. - David J. Albers; Matthew E. Levine; Bruce J. Gluckman; Henry N. Ginsberg; George Hripcsak; Lena Mamykina (PLoS Comput. Biol., 2017)

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 (AMIA, 2018)

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 (CHI, 2018)

Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype. - David J. Albers; Matthew E. Levine; Andrew M. Stuart; Lena Mamykina; Bruce J. Gluckman; George Hripcsak (J. Am. Medical Informatics Assoc., 2018)

A visual analytics approach for pattern-recognition in patient-generated data. - Daniel J. Feller; Marissa Burgermaster; Matthew E. Levine; Arlene M. Smaldone; Patricia G. Davidson; David J. Albers; Lena Mamykina (J. Am. Medical Informatics Assoc., 2018)

High-fidelity phenotyping: richness and freedom from bias. - George Hripcsak; David J. Albers (J. Am. Medical Informatics Assoc., 2018)

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms. - David J. Albers; Noémie Elhadad; Jan Claassen; Rimma Perotte; Andrew Goldstein; George Hripcsak (J. Biomed. Informatics, 2018)

Methodological variations in lagged regression for detecting physiologic drug effects in EHR data. - Matthew E. Levine; David J. Albers; George Hripcsak (J. Biomed. Informatics, 2018)

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 (AMIA, 2019)

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 (AMIA, 2019)

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; et al. (AMIA, 2019)

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 (CHI, 2019)

Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics. - Iñigo Urteaga; Tristan Bertin; Theresa M. Hardy; David J. Albers; Noémie Elhadad (MLHC, 2019)

Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. - Ashenafi Zebene Woldaregay; Eirik Årsand; Ståle Walderhaug; David J. Albers; Lena Mamykina; Taxiarchis Botsis; Gunnar Hartvigsen (Artif. Intell. Medicine, 2019)

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 (AMIA, 2020)

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 (AMIA, 2020)

A new approach to integrating patient-generated data with expert knowledge for personalized goal setting: A pilot study. - 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 (Int. J. Medical Informatics, 2020)

Development and validation of early warning score system: A systematic literature review. - 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 (J. Biomed. Informatics, 2020)

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 (AMIA, 2021)

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 (CHI Extended Abstracts, 2021)

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; et al. (CHI, 2021)

Identifying nursing documentation patterns associated with patient deterioration and recovery from deterioration in critical and acute care settings. - 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 007; Jeffrey G. Klann; Kenrick Cato; et al. (Int. J. Medical Informatics, 2021)

Utilizing timestamps of longitudinal electronic health record data to classify clinical deterioration events. - Li-heng Fu; Chris Knaplund; Kenrick Cato; Adler J. Perotte; Min-Jeoung Kang; Patricia C. Dykes; David J. Albers; Sarah Collins Rossetti (J. Am. Medical Informatics Assoc., 2021)

Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework. - Sarah Collins Rossetti; Chris Knaplund; David J. Albers; Patricia C. Dykes; Min-Jeoung Kang; Zfania Tom Korach; Li Zhou 007; Kumiko Schnock; Jose P. Garcia; Jessica M. Schwartz; Li-heng Fu; Jeffrey G. Klann; et al. (J. Am. Medical Informatics Assoc., 2021)

Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study. - 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; et al. (J. Am. Medical Informatics Assoc., 2021)

Enabling personalized decision support with patient-generated data and attributable components. - Elliot G. Mitchell; Esteban G. Tabak; Matthew E. Levine; Lena Mamykina; David J. Albers (J. Biomed. Informatics, 2021)

Correction: Personalized glucose forecasting for type 2 diabetes using data assimilation. - David J. Albers; Matthew E. Levine; Bruce J. Gluckman; Henry N. Ginsberg; George Hripcsak; Lena Mamykina (PLoS Comput. Biol., 2021)

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 (AMIA, 2022)

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 (AMIA, 2022)

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 (AMIA, 2022)

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 (AMIA, 2022)

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 (AMIA, 2022)

Hypothesis-driven modeling of the human lung-ventilator system: A characterization tool for Acute Respiratory Distress Syndrome research. - J. N. Stroh; Bradford J. Smith; Peter D. Sottile; George Hripcsak; David J. Albers (J. Biomed. Informatics, 2023)

Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity. - 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 (J. Biomed. Informatics, 2023)

Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data. - David J. Albers; Melike Sirlanci; Matthew E. Levine; Jan Claassen; Caroline Der Nigoghossian; George Hripcsak (J. Biomed. Informatics, 2023)

A methodology of phenotyping ICU patients from EHR data: High-fidelity, personalized, and interpretable phenotypes estimation. - 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 (J. Biomed. Informatics, 2023)

Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model. - Deepak K. Agrawal; Bradford J. Smith; Peter D. Sottile; George Hripcsak; David J. Albers (Comput. Biol. Medicine, 2024)

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 (CHI Extended Abstracts, 2025)

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 (CHI, 2025)