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Data-driven analysis to understand long COVID using electronic health records from th... | RTCL.TV
### Keywords ###
#authorscharacterise #characterisepostacute #postacutesequelae #electronichealth #healthrecords #PASC #largecohorts #RTCLTV #shorts
### Article Attribution ###
Title: Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative
Authors: Chengxi Zang, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Edward J. Schenck, Dhruv Khullar, Anna S. Nordvig, Elizabeth A. Shenkman, Russell L. Rothman, Jason P. Block, Kristin Lyman, Mark G. Weiner, Thomas W. Carton, Fei Wang ,and Rainu Kaushal
Publisher: Nature Portfolio
DOI: 10.1038/s41467-023-37653-z
DOAJ URL: https://doaj.org/article/a9085741976a4ea2ab2508dda6b0f2c7
Source URL: https://doi.org/10.1038/s41467-023-37653-z
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#authorscharacterise #characterisepostacute #postacutesequelae #electronichealth #healthrecords #PASC #largecohorts #RTCLTV #shorts
### Article Attribution ###
Title: Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative
Authors: Chengxi Zang, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Edward J. Schenck, Dhruv Khullar, Anna S. Nordvig, Elizabeth A. Shenkman, Russell L. Rothman, Jason P. Block, Kristin Lyman, Mark G. Weiner, Thomas W. Carton, Fei Wang ,and Rainu Kaushal
Publisher: Nature Portfolio
DOI: 10.1038/s41467-023-37653-z
DOAJ URL: https://doaj.org/article/a9085741976a4ea2ab2508dda6b0f2c7
Source URL: https://doi.org/10.1038/s41467-023-37653-z
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