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Learning from data: A recurring feature on the science and practice of data‐driven learning health systems
dc.contributor.authorEmbi, Peter J.
dc.contributor.authorPayne, Philip R. O.
dc.contributor.authorFriedman, Charles P.
dc.date.accessioned2022-02-07T20:22:12Z
dc.date.available2023-02-07 15:22:11en
dc.date.available2022-02-07T20:22:12Z
dc.date.issued2022-01
dc.identifier.citationEmbi, Peter J.; Payne, Philip R. O.; Friedman, Charles P. (2022). "Learning from data: A recurring feature on the science and practice of data‐driven learning health systems." Learning Health Systems 6(1): n/a-n/a.
dc.identifier.issn2379-6146
dc.identifier.issn2379-6146
dc.identifier.urihttps://hdl.handle.net/2027.42/171523
dc.publisherWiley Periodicals, Inc.
dc.titleLearning from data: A recurring feature on the science and practice of data‐driven learning health systems
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBiomedical Health Sciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/171523/1/lrh210302_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/171523/2/lrh210302.pdf
dc.identifier.doi10.1002/lrh2.10302
dc.identifier.sourceLearning Health Systems
dc.identifier.citedreferenceMaddox TM, Rumsfeld JS, Payne PRO. Questions for artificial intelligence in health care. JAMA. 2019; 321 ( 1 ): 31 ‐ 32.
dc.identifier.citedreferenceEmbi PJ. Algorithmovigilance‐advancing methods to analyze and monitor artificial intelligence‐driven health care for effectiveness and equity. JAMA Netw Open. 2021; 4 ( 4 ): e214622.
dc.identifier.citedreferenceFriedman CP, Allee NJ, Delaney BC, et al. The science of learning health systems: foundations for a new journal. Learn Health Syst. 2017; 1 ( 1 ): e10020.
dc.identifier.citedreferenceFriedman C, Rubin J, Brown J, et al. Toward a science of learning systems: a research agenda for the high‐functioning learning health system. J Am Med Inform Assoc. 2015; 22 ( 1 ): 43 ‐ 50.
dc.identifier.citedreferenceEmbi PJ, Payne PR. Advancing methodologies in clinical research informatics (CRI): foundational work for a maturing field. J Biomed Inform. 2014; 52: 1 ‐ 3.
dc.identifier.citedreferenceEmbi PJ, Payne PR. Clinical research informatics: challenges, opportunities and definition for an emerging domain. J Am Med Inform Assoc. 2009; 16 ( 3 ): 316 ‐ 327.
dc.identifier.citedreferenceMadhavan S, Bastarache L, Brown JS, et al. Use of electronic health records to support a public health response to the COVID‐19 pandemic in the United States: a perspective from 15 academic medical centers. J Am Med Inform Assoc. 2021; 28 ( 2 ): 393 ‐ 401.
dc.identifier.citedreferenceHersh WR, Weiner MG, Embi PJ, et al. Caveats for the use of operational electronic health record data in comparative effectiveness research. Med Care. 2013; 51 ( 8 Suppl 3 ): S30 ‐ S37.
dc.identifier.citedreferenceBastarache L, Brown JS, Cimino JJ, et al. Developing real‐world evidence from real‐world data: transforming raw data into analytical datasets. Learn Health Syst. 2022; 6 ( 1 ): e10293.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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