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Performance of an automated deep learning algorithm to iden..:
Torgersen, Jessie
;
Akers, Scott
;
Huo, Yuankai
...
Pharmacoepidemiology and Drug Safety. 32 (2023) 10 - p. 1121-1130 , 2023
Link:
https://doi.org/10.1002/pds.5648
RT Journal T1 <Title>Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1002_pds.5648&Exemplar=1&LAN=DE A1 Torgersen, Jessie A1 Akers, Scott A1 Huo, Yuankai A1 Terry, James G. A1 Carr, J. Jeffrey A1 Ruutiainen, Alexander T. A1 Skanderson, Melissa A1 Levin, Woody A1 Lim, Joseph K. A1 Taddei, Tamar H. A1 So‐Armah, Kaku A1 Bhattacharya, Debika A1 Rentsch, Christopher T. A1 Shen, Li A1 Carr, Rotonya A1 Shinohara, Russell T. A1 McClain, Michele A1 Freiberg, Matthew A1 Justice, Amy C. A1 Lo Re III, Vincent PB Wiley YR 2023 SN 1053-8569 SN 1099-1557 JF Pharmacoepidemiology and Drug Safety VO 32 IS 10 SP 1121 OP 1130 LK http://dx.doi.org/https://doi.org/10.1002/pds.5648 DO https://doi.org/10.1002/pds.5648 SF ELIB - SuUB Bremen
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