 Connection
David Albers to Data Mining
This is a "connection" page, showing publications David Albers has written about Data Mining.
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Connection Strength |
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1.386 |
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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: 0.523
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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: 0.359
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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: 0.137
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Pivovarov R, Albers DJ, Sepulveda JL, Elhadad N. Identifying and mitigating biases in EHR laboratory tests. J Biomed Inform. 2014 Oct; 51:24-34.
Score: 0.100
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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: 0.096
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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: 0.085
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Woldaregay AZ, Årsand 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: 0.036
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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: 0.027
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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: 0.023
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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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