David J. Albers

Orcid: 0000-0002-5369-526X

According to our database1, David J. Albers authored at least 57 papers between 2011 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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On csauthors.net:

Bibliography

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

Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data.
J. Biomed. Informatics, September, 2023

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

Hypothesis-driven modeling of the human lung-ventilator system: A characterization tool for Acute Respiratory Distress Syndrome research.
J. Biomed. Informatics, January, 2023

2022
A methodology of phenotyping ICU patients: high-fidelity, personalized, and interpretable phenotypes estimation.
Proceedings of the AMIA 2022, 2022

Gaining Purchase on Ventilator-Induced Lung Injury: A Interpretable Approach to Describing Complex System Data via Informed Modeling.
Proceedings of the AMIA 2022, 2022

Using Data Assimilation to Predict Post-Operative Bariatric Surgery Glycemic Status in Adolescents.
Proceedings of the AMIA 2022, 2022

Informatics Research and Implementation During COVID: Challenges, Opportunities and Recommendations for Building a Sustainable Infrastructure.
Proceedings of the AMIA 2022, 2022

Optimizing Strategies of Pressure Reactivity Index and Optimal Cerebral Perfusion Pressure Identification for Cerebral Autoregulatory-Guided Clinical Decision Support.
Proceedings of the AMIA 2022, 2022

2021
Correction: Personalized glucose forecasting for type 2 diabetes using data assimilation.
PLoS Comput. Biol., 2021

Enabling personalized decision support with patient-generated data and attributable components.
J. Biomed. Informatics, 2021

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

Utilizing timestamps of longitudinal electronic health record data to classify clinical deterioration events.
J. Am. Medical Informatics Assoc., 2021

Identifying nursing documentation patterns associated with patient deterioration and recovery from deterioration in critical and acute care settings.
Int. J. Medical Informatics, 2021

From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Scaling Up HCI Research: from Clinical Trials to Deployment in the Wild.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Toward phenotyping of ventilator-induced lung injury with a damage-informed pulmonary model of lung-ventilator interaction.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

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

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

Utilizing Timestamps of Longitudinal Data from Electronic Health Record to Predict Clinical Deterioration Events.
Proceedings of the AMIA 2020, 2020

Lessons learned from assimilating knowledge into machine learning to forecast and control glucose in a critical care setting.
Proceedings of the AMIA 2020, 2020

2019
Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
Artif. Intell. Medicine, 2019

Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics.
Proceedings of the Machine Learning for Healthcare Conference, 2019

Personal Health Oracle: Explorations of Personalized Predictions in Diabetes Self-Management.
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Leveraging Clinical Expertise as a Feature - not an Outcome - of Predictive Models: Evaluation of an Early Warning System Use Case.
Proceedings of the AMIA 2019, 2019

Machine learning for personalized decision support with patient-generated health data.
Proceedings of the AMIA 2019, 2019

Feasibility of a machine learning based method to generate personalized nutrition goals for diabetes self-management.
Proceedings of the AMIA 2019, 2019

2018
Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.
J. Biomed. Informatics, 2018

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.
J. Biomed. Informatics, 2018

High-fidelity phenotyping: richness and freedom from bias.
J. Am. Medical Informatics Assoc., 2018

A visual analytics approach for pattern-recognition in patient-generated data.
J. Am. Medical Informatics Assoc., 2018

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., 2018

Pictures Worth a Thousand Words: Reflections on Visualizing Personal Blood Glucose Forecasts for Individuals with Type 2 Diabetes.
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018

Using mechanistic machine learning to forecast glucose and infer physiologic phenotypes in the ICU: what is possible and what are the challenges.
Proceedings of the AMIA 2018, 2018

2017
Personalized glucose forecasting for type 2 diabetes using data assimilation.
PLoS Comput. Biol., 2017

An Interoperable Similarity-based Cohort Identification Method Using the OMOP Common Data Model Version 5.0.
J. Heal. Informatics Res., 2017

Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes.
CoRR, 2017

Reflecting on Diabetes Self-Management Logs with Simulated, Continuous Blood Glucose Curves: A Pilot Study.
Proceedings of the AMIA 2017, 2017

Why predicting postprandial glucose using self-monitoring data is difficult.
Proceedings of the AMIA 2017, 2017

2016
Data-driven health management: reasoning about personally generated data in diabetes with information technologies.
J. Am. Medical Informatics Assoc., 2016

Comparing Lagged Linear Correlation, Lagged Regression, Granger Causality, and Vector Autoregression for Uncovering Associations in EHR Data.
Proceedings of the AMIA 2016, 2016

Approaches for using temporal and other filters for next generation phenotype discovery.
Proceedings of the AMIA 2016, 2016

Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes.
Proceedings of the AMIA 2016, 2016

2015
Parameterizing time in electronic health record studies.
J. Am. Medical Informatics Assoc., 2015

Model Selection For EHR Laboratory Tests Preserving Healthcare Context and Underlying Physiology.
Proceedings of the AMIA 2015, 2015

Personalized medicine beyond genetics: using personalized model-based forecasting to help type 2 diabetics understand and predict their post-meal glucose.
Proceedings of the AMIA 2015, 2015

2014
Survival analysis with electronic health record data: Experiments with chronic kidney disease.
Stat. Anal. Data Min., 2014

Identifying and mitigating biases in EHR laboratory tests.
J. Biomed. Informatics, 2014

Temporal trends of hemoglobin A1c testing.
J. Am. Medical Informatics Assoc., 2014

Model selection for EHR laboratory variables: how physiology and the health care process can influence EHR laboratory data and their model representations.
Proceedings of the AMIA 2014, 2014

2013
Next-generation phenotyping of electronic health records.
J. Am. Medical Informatics Assoc., 2013

Using patient laboratory measurement values and dynamics to deconvolve EHR bias and define acuity-based phenotypes.
Proceedings of the AMIA 2013, 2013

2012
Data assimilation of glucose dynamics for use in the intensive care unit.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Using Empirical orthogonal functions to identify temporally important variables to understand time-dependent pathophysiologic and phenotypic differences in patients.
Proceedings of the AMIA 2012, 2012

2011
Exploiting time in electronic health record correlations.
J. Am. Medical Informatics Assoc., 2011

Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations
CoRR, 2011


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