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Connection

David Albers to Models, Statistical

This is a "connection" page, showing publications David Albers has written about Models, Statistical.

 
Connection Strength
 
 
 
1.255
 
  1. 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.
    View in: PubMed
    Score: 0.508
  2. 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.
    View in: PubMed
    Score: 0.303
  3. 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.
    View in: PubMed
    Score: 0.114
  4. 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.
    View in: PubMed
    Score: 0.107
  5. 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.
    View in: PubMed
    Score: 0.089
  6. Albers DJ, Hripcsak G, Schmidt M. Population physiology: leveraging electronic health record data to understand human endocrine dynamics. PLoS One. 2012; 7(12):e48058.
    View in: PubMed
    Score: 0.080
  7. 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.
    View in: PubMed
    Score: 0.033
  8. 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.
    View in: PubMed
    Score: 0.022
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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