 Connection
David Albers to Algorithms
This is a "connection" page, showing publications David Albers has written about Algorithms.
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Connection Strength |
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1.270 |
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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: 0.542
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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: 0.363
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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: 0.120
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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: 0.091
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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: 0.086
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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: 0.026
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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: 0.025
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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: 0.018
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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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