 Connection
David Albers to Humans
This is a "connection" page, showing publications David Albers has written about Humans.
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Connection Strength |
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0.436 |
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Agrawal DK, Smith BJ, Sottile PD, Hripcsak G, Albers DJ. Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model. Comput Biol Med. 2024 05; 173:108349.
Score: 0.023
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Wang Y, Stroh JN, Hripcsak G, Low Wang CC, Bennett TD, Wrobel J, Der Nigoghossian C, Mueller SW, Claassen J, Albers DJ. A methodology of phenotyping ICU patients from EHR data: High-fidelity, personalized, and interpretable phenotypes estimation. J Biomed Inform. 2023 12; 148:104547.
Score: 0.023
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Albers D, Sirlanci M, Levine M, Claassen J, Nigoghossian C, Hripcsak G. Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data. J Biomed Inform. 2023 09; 145:104477.
Score: 0.022
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Graham EJ, Elhadad N, Albers D. Reduced model for female endocrine dynamics: Validation and functional variations. Math Biosci. 2023 04; 358:108979.
Score: 0.021
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Stroh JN, Smith BJ, Sottile PD, Hripcsak G, Albers DJ. Hypothesis-driven modeling of the human lung-ventilator system: A characterization tool for Acute Respiratory Distress Syndrome research. J Biomed Inform. 2023 01; 137:104275.
Score: 0.021
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Hripcsak G, Albers DJ. Evaluating Prediction of Continuous Clinical Values: A Glucose Case Study. Methods Inf Med. 2022 06; 61(S 01):e35-e44.
Score: 0.020
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Bennett TD, Russell S, Albers DJ. Neural Networks for Mortality Prediction: Ready for Prime Time? Pediatr Crit Care Med. 2021 06 01; 22(6):578-581.
Score: 0.019
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Mitchell EG, Tabak EG, Levine ME, Mamykina L, Albers DJ. Enabling personalized decision support with patient-generated data and attributable components. J Biomed Inform. 2021 01; 113:103639.
Score: 0.018
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Albers DJ, Levine ME, Mamykina L, Hripcsak G. The parameter Houlihan: A solution to high-throughput identifiability indeterminacy for brutally ill-posed problems. Math Biosci. 2019 10; 316:108242.
Score: 0.017
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Albers DJ, Levine ME, Stuart A, Mamykina L, Gluckman B, Hripcsak G. Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype. J Am Med Inform Assoc. 2018 10 01; 25(10):1392-1401.
Score: 0.016
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Albers DJ, Elhadad N, Claassen J, Perotte R, Goldstein A, Hripcsak G. Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms. J Biomed Inform. 2018 02; 78:87-101.
Score: 0.015
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Albers DJ, Levine M, Gluckman B, Ginsberg H, Hripcsak G, Mamykina L. Personalized glucose forecasting for type 2 diabetes using data assimilation. PLoS Comput Biol. 2017 04; 13(4):e1005232.
Score: 0.014
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Mamykina L, Levine ME, Davidson PG, Smaldone AM, Elhadad N, Albers DJ. Data-driven health management: reasoning about personally generated data in diabetes with information technologies. J Am Med Inform Assoc. 2016 05; 23(3):526-31.
Score: 0.013
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Albers DJ, Elhadad N, Tabak E, Perotte A, Hripcsak G. Dynamical phenotyping: using temporal analysis of clinically collected physiologic data to stratify populations. PLoS One. 2014; 9(6):e96443.
Score: 0.012
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Hripcsak G, Albers DJ. Correlating electronic health record concepts with healthcare process events. J Am Med Inform Assoc. 2013 Dec; 20(e2):e311-8.
Score: 0.011
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Albers DJ, Hripcsak G, Schmidt M. Population physiology: leveraging electronic health record data to understand human endocrine dynamics. PLoS One. 2012; 7(12):e48058.
Score: 0.011
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Hripcsak G, Albers DJ. Next-generation phenotyping of electronic health records. J Am Med Inform Assoc. 2013 Jan 01; 20(1):117-21.
Score: 0.010
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Albers DJ, Hripcsak G. Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations. Chaos. 2012 Mar; 22(1):013111.
Score: 0.010
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Martin B, DeWitt PE, Payan M, Greer CH, Russell S, Gray C, Deakyne Davies SJ, Woods-Hill CZ, Scott HF, Parker S, Albers D, Bennett TD. Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning. Hosp Pediatr. 2025 Jun 01; 15(6):e240-e244.
Score: 0.006
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Martin B, DeWitt PE, Russell S, Haendel M, Sanchez-Pinto N, Albers DJ, Jhaveri RR, Moffitt R, Bennett TD. The Recent Increase in Invasive Bacterial Infections: A Report From the National COVID Cohort Collaborative. Pediatr Infect Dis J. 2025 Mar 01; 44(3):217-227.
Score: 0.006
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Schlapbach LJ, Watson RS, Sorce LR, Argent AC, Menon K, Hall MW, Akech S, Albers DJ, Alpern ER, Balamuth F, Bembea M, Biban P, Carrol ED, Chiotos K, Chisti MJ, DeWitt PE, Evans I, Flauzino de Oliveira C, Horvat CM, Inwald D, Ishimine P, Jaramillo-Bustamante JC, Levin M, Lodha R, Martin B, Nadel S, Nakagawa S, Peters MJ, Randolph AG, Ranjit S, Rebull MN, Russell S, Scott HF, de Souza DC, Tissieres P, Weiss SL, Wiens MO, Wynn JL, Kissoon N, Zimmerman JJ, Sanchez-Pinto LN, Bennett TD. International Consensus Criteria for Pediatric Sepsis and Septic Shock. JAMA. 2024 02 27; 331(8):665-674.
Score: 0.006
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Sanchez-Pinto LN, Bennett TD, DeWitt PE, Russell S, Rebull MN, Martin B, Akech S, Albers DJ, Alpern ER, Balamuth F, Bembea M, Chisti MJ, Evans I, Horvat CM, Jaramillo-Bustamante JC, Kissoon N, Menon K, Scott HF, Weiss SL, Wiens MO, Zimmerman JJ, Argent AC, Sorce LR, Schlapbach LJ, Watson RS, Biban P, Carrol E, Chiotos K, Flauzino De Oliveira C, Hall MW, Inwald D, Ishimine P, Levin M, Lodha R, Nadel S, Nakagawa S, Peters MJ, Randolph AG, Ranjit S, Souza DC, Tissieres P, Wynn JL. Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock. JAMA. 2024 02 27; 331(8):675-686.
Score: 0.006
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Sottile PD, Smith B, Stroh JN, Albers DJ, Moss M. Flow-Limited and Reverse-Triggered Ventilator Dyssynchrony Are Associated With Increased Tidal and Dynamic Transpulmonary Pressure. Crit Care Med. 2024 05 01; 52(5):743-751.
Score: 0.006
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Briggs JK, Gresch A, Marinelli I, Dwulet JM, Albers DJ, Kravets V, Benninger RKP. ?-cell intrinsic dynamics rather than gap junction structure dictates subpopulations in the islet functional network. Elife. 2023 Nov 29; 12.
Score: 0.006
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Sirlanci M, Levine ME, Low Wang CC, Albers DJ, Stuart AM. A simple modeling framework for prediction in the human glucose-insulin system. Chaos. 2023 Jul 01; 33(7).
Score: 0.005
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Burgermaster M, Desai PM, Heitkemper EM, Juul F, Mitchell EG, Turchioe M, Albers DJ, Levine ME, Larson D, Mamykina L. Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity. J Biomed Inform. 2023 08; 144:104419.
Score: 0.005
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Martin B, DeWitt PE, Albers D, Bennett TD. Development of a Pediatric Blood Pressure Percentile Tool for Clinical Decision Support. JAMA Netw Open. 2022 10 03; 5(10):e2236918.
Score: 0.005
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Sottile PD, Albers D, DeWitt PE, Russell S, Stroh JN, Kao DP, Adrian B, Levine ME, Mooney R, Larchick L, Kutner JS, Wynia MK, Glasheen JJ, Bennett TD. Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study. J Am Med Inform Assoc. 2021 10 12; 28(11):2354-2365.
Score: 0.005
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Fu LH, Knaplund C, Cato K, Perotte A, Kang MJ, Dykes PC, Albers D, Collins Rossetti S. Utilizing timestamps of longitudinal electronic health record data to classify clinical deterioration events. J Am Med Inform Assoc. 2021 08 13; 28(9):1955-1963.
Score: 0.005
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Stroh JN, Albers DJ, Bennett TD. Personalization and Pragmatism: Pediatric Intracranial Pressure and Cerebral Perfusion Pressure Treatment Thresholds. Pediatr Crit Care Med. 2021 02 01; 22(2):213-216.
Score: 0.005
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Karamched B, Hripcsak G, Albers D, Ott W. Delay-induced uncertainty for a paradigmatic glucose-insulin model. Chaos. 2021 Feb; 31(2):023142.
Score: 0.005
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Burgermaster M, Son JH, Davidson PG, Smaldone AM, Kuperman G, Feller DJ, Burt KG, Levine ME, Albers DJ, Weng C, Mamykina L. A new approach to integrating patient-generated data with expert knowledge for personalized goal setting: A pilot study. Int J Med Inform. 2020 07; 139:104158.
Score: 0.004
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Fu LH, Schwartz J, Moy A, Knaplund C, Kang MJ, Schnock KO, Garcia JP, Jia H, Dykes PC, Cato K, Albers D, Rossetti SC. Development and validation of early warning score system: A systematic literature review. J Biomed Inform. 2020 05; 105:103410.
Score: 0.004
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Woldaregay AZ, ?rsand E, Walderhaug S, Albers D, Mamykina L, Botsis T, Hartvigsen G. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. Artif Intell Med. 2019 07; 98:109-134.
Score: 0.004
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Roh DJ, Albers DJ, Magid-Bernstein J, Doyle K, Hod E, Eisenberger A, Murthy S, Witsch J, Park S, Agarwal S, Connolly ES, Elkind MSV, Claassen J. Low hemoglobin and hematoma expansion after intracerebral hemorrhage. Neurology. 2019 07 23; 93(4):e372-e380.
Score: 0.004
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Woldaregay AZ, ?rsand E, Botsis T, Albers D, Mamykina L, Hartvigsen G. Data-Driven Blood Glucose Pattern Classification and Anomalies Detection: Machine-Learning Applications in Type 1 Diabetes. J Med Internet Res. 2019 05 01; 21(5):e11030.
Score: 0.004
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Feller DJ, Burgermaster M, Levine ME, Smaldone A, Davidson PG, Albers DJ, Mamykina L. A visual analytics approach for pattern-recognition in patient-generated data. J Am Med Inform Assoc. 2018 10 01; 25(10):1366-1374.
Score: 0.004
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Levine ME, Albers DJ, Hripcsak G. Methodological variations in lagged regression for detecting physiologic drug effects in EHR data. J Biomed Inform. 2018 10; 86:149-159.
Score: 0.004
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Sottile PD, Albers D, Moss MM. Neuromuscular blockade is associated with the attenuation of biomarkers of epithelial and endothelial injury in patients with moderate-to-severe acute respiratory distress syndrome. Crit Care. 2018 Mar 10; 22(1):63.
Score: 0.004
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Sottile PD, Albers D, Higgins C, Mckeehan J, Moss MM. The Association Between Ventilator Dyssynchrony, Delivered Tidal Volume, and Sedation Using a Novel Automated Ventilator Dyssynchrony Detection Algorithm. Crit Care Med. 2018 02; 46(2):e151-e157.
Score: 0.004
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Foreman B, Albers D, Schmidt JM, Falo CM, Velasquez A, Connolly ES, Claassen J. Intracortical electrophysiological correlates of blood flow after severe SAH: A multimodality monitoring study. J Cereb Blood Flow Metab. 2018 03; 38(3):506-517.
Score: 0.004
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Levine ME, Albers DJ, Hripcsak G. Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data. AMIA Annu Symp Proc. 2016; 2016:779-788.
Score: 0.004
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Claassen J, Rahman SA, Huang Y, Frey HP, Schmidt JM, Albers D, Falo CM, Park S, Agarwal S, Connolly ES, Kleinberg S. Causal Structure of Brain Physiology after Brain Injury from Subarachnoid Hemorrhage. PLoS One. 2016; 11(4):e0149878.
Score: 0.003
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Hripcsak G, Albers DJ, Perotte A. Parameterizing time in electronic health record studies. J Am Med Inform Assoc. 2015 Jul; 22(4):794-804.
Score: 0.003
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Pivovarov R, Albers DJ, Hripcsak G, Sepulveda JL, Elhadad N. Temporal trends of hemoglobin A1c testing. J Am Med Inform Assoc. 2014 Nov-Dec; 21(6):1038-44.
Score: 0.003
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Schmidt JM, Sow D, Crimmins M, Albers D, Agarwal S, Claassen J, Connolly ES, Elkind MS, Hripcsak G, Mayer SA. Heart rate variability for preclinical detection of secondary complications after subarachnoid hemorrhage. Neurocrit Care. 2014 Jun; 20(3):382-9.
Score: 0.003
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Claassen J, Albers D, Schmidt JM, De Marchis GM, Pugin D, Falo CM, Mayer SA, Cremers S, Agarwal S, Elkind MS, Connolly ES, Dukic V, Hripcsak G, Badjatia N. Nonconvulsive seizures in subarachnoid hemorrhage link inflammation and outcome. Ann Neurol. 2014 May; 75(5):771-81.
Score: 0.003
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Claassen J, Perotte A, Albers D, Kleinberg S, Schmidt JM, Tu B, Badjatia N, Lantigua H, Hirsch LJ, Mayer SA, Connolly ES, Hripcsak G. Nonconvulsive seizures after subarachnoid hemorrhage: Multimodal detection and outcomes. Ann Neurol. 2013 Jul; 74(1):53-64.
Score: 0.003
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Boland MR, Hripcsak G, Albers DJ, Wei Y, Wilcox AB, Wei J, Li J, Lin S, Breene M, Myers R, Zimmerman J, Papapanou PN, Weng C. Discovering medical conditions associated with periodontitis using linked electronic health records. J Clin Periodontol. 2013 May; 40(5):474-82.
Score: 0.003
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Sedigh-Sarvestani M, Albers DJ, Gluckman BJ. Data assimilation of glucose dynamics for use in the intensive care unit. Annu Int Conf IEEE Eng Med Biol Soc. 2012; 2012:5437-40.
Score: 0.002
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Hripcsak G, Albers DJ, Perotte A. Exploiting time in electronic health record correlations. J Am Med Inform Assoc. 2011 Dec; 18 Suppl 1:i109-15.
Score: 0.002
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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