 Connection
David Albers to Models, Biological
This is a "connection" page, showing publications David Albers has written about Models, Biological.
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Connection Strength |
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1.118 |
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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: 0.403
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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: 0.379
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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: 0.240
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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: 0.070
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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: 0.025
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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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