De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository.
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%0 Journal Article
%1 journals/jamia/PfaffGCGMWKWHBLCMH23
%A Pfaff, Emily R.
%A Girvin, Andrew T.
%A Crosskey, Miles
%A Gangireddy, Srushti
%A Master, Hiral
%A Wei, Wei-Qi
%A Kerchberger, Vern Eric
%A Weiner, Mark G.
%A Harris, Paul A.
%A Basford, Melissa A.
%A Lunt, Christopher
%A Chute, Christopher G.
%A Moffitt, Richard A.
%A Haendel, Melissa A.
%D 2023
%J J. Am. Medical Informatics Assoc.
%K dblp
%N 7
%P 1305-1312
%T De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository.
%U http://dblp.uni-trier.de/db/journals/jamia/jamia30.html#PfaffGCGMWKWHBLCMH23
%V 30
@article{journals/jamia/PfaffGCGMWKWHBLCMH23,
added-at = {2023-09-30T00:00:00.000+0200},
author = {Pfaff, Emily R. and Girvin, Andrew T. and Crosskey, Miles and Gangireddy, Srushti and Master, Hiral and Wei, Wei-Qi and Kerchberger, Vern Eric and Weiner, Mark G. and Harris, Paul A. and Basford, Melissa A. and Lunt, Christopher and Chute, Christopher G. and Moffitt, Richard A. and Haendel, Melissa A.},
biburl = {https://www.bibsonomy.org/bibtex/23a0ecb6653a6156a5f14c914f702c861/dblp},
ee = {https://doi.org/10.1093/jamia/ocad077},
interhash = {2b926d105f8f8d8be10231cde6281ba0},
intrahash = {3a0ecb6653a6156a5f14c914f702c861},
journal = {J. Am. Medical Informatics Assoc.},
keywords = {dblp},
month = {June},
number = 7,
pages = {1305-1312},
timestamp = {2024-04-08T17:14:18.000+0200},
title = {De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository.},
url = {http://dblp.uni-trier.de/db/journals/jamia/jamia30.html#PfaffGCGMWKWHBLCMH23},
volume = 30,
year = 2023
}