Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.
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%0 Journal Article
%1 journals/jamia/AlbersLSMGH18
%A Albers, David J.
%A Levine, Matthew E.
%A Stuart, Andrew M.
%A Mamykina, Lena
%A Gluckman, Bruce J.
%A Hripcsak, George
%D 2018
%J J. Am. Medical Informatics Assoc.
%K dblp
%N 10
%P 1392-1401
%T Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.
%U http://dblp.uni-trier.de/db/journals/jamia/jamia25.html#AlbersLSMGH18
%V 25
@article{journals/jamia/AlbersLSMGH18,
added-at = {2021-10-14T00:00:00.000+0200},
author = {Albers, David J. and Levine, Matthew E. and Stuart, Andrew M. and Mamykina, Lena and Gluckman, Bruce J. and Hripcsak, George},
biburl = {https://www.bibsonomy.org/bibtex/2732262604f4f8093b850f8fd3fb9de61/dblp},
ee = {https://www.wikidata.org/entity/Q57487381},
interhash = {59345ddfd758eb04c048127ddde4a672},
intrahash = {732262604f4f8093b850f8fd3fb9de61},
journal = {J. Am. Medical Informatics Assoc.},
keywords = {dblp},
number = 10,
pages = {1392-1401},
timestamp = {2024-04-08T17:13:16.000+0200},
title = {Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.},
url = {http://dblp.uni-trier.de/db/journals/jamia/jamia25.html#AlbersLSMGH18},
volume = 25,
year = 2018
}
