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Computable knowledge: An imperative for Learning Health Systems
dc.contributor.authorFriedman, Charles P.
dc.contributor.authorFlynn, Allen J.
dc.date.accessioned2019-11-12T16:21:57Z
dc.date.availableWITHHELD_12_MONTHS
dc.date.available2019-11-12T16:21:57Z
dc.date.issued2019-10
dc.identifier.citationFriedman, Charles P.; Flynn, Allen J. (2019). "Computable knowledge: An imperative for Learning Health Systems." Learning Health Systems 3(4): n/a-n/a.
dc.identifier.issn2379-6146
dc.identifier.issn2379-6146
dc.identifier.urihttps://hdl.handle.net/2027.42/151989
dc.publisherSpringer
dc.publisherWiley Periodicals, Inc.
dc.titleComputable knowledge: An imperative for Learning Health Systems
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBiomedical Health Sciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/151989/1/lrh210203.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/151989/2/lrh210203_am.pdf
dc.identifier.doi10.1002/lrh2.10203
dc.identifier.sourceLearning Health Systems
dc.identifier.citedreferencehttps://medicine.umich.edu/dept/lhs/2018-mcbk-meeting, Accessed.
dc.identifier.citedreferenceBates DW, Saria S, Ohno‐Machado L, Shah A, Escobar G. Big data in health care: using analytics to identify and manage high‐risk and high‐cost patients. Health Aff. 2014; 33 ( 7 ): 1123 ‐ 1131.
dc.identifier.citedreferenceGuise JM, Savitz LA, Friedman CP. Mind the gap: putting evidence into practice in the era of learning health systems. J Gen Intern Med. 2018; 33 ( 12 ): 2237 ‐ 2239.
dc.identifier.citedreferenceAdler‐Milstein J, Nong P, Friedman CP. Preparing healthcare delivery organizations for managing computable knowledge. Learning Health Syst. 2019; 3 ( 2 ): e10070.
dc.identifier.citedreferenceNational Library of Medicine. A platform for biomedical discovery and data‐powered health: National Library of Medicine Strategic Plan 2017–2027. US Department of Health and Human Services National Insitute of Health 2017.
dc.identifier.citedreferenceSomers J. The scientific paper is obsolete. The Atlantic. 2018.
dc.identifier.citedreferenceFlynn AJ. (in press) Theory of advice as an information object targeted at an unmade decision. Journal of Documentation
dc.identifier.citedreferenceGoble C, De Roure D, Bechhofer S. Accelerating scientists’ knowledge turns. In: International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management. Berlin, Heidelberg: Springer; 2011: 3 ‐ 25.
dc.identifier.citedreferencehttp://mobilizecbk.org. Accessed.
dc.identifier.citedreferencehttps://medicine.umich.edu/dept/lhs/2019-mcbk-meeting, Accessed.
dc.identifier.citedreferenceHigh R. The era of cognitive systems: An inside look at IBM Watson and how it works. Armonk, New York: IBM Corporation, Redbooks; Dec. 12 2012.
dc.identifier.citedreferenceFriedman CP, Rubin JC, Sullivan KJ. Toward an information infrastructure for Global Health Improvement. Yearb Med Inform. 2017; 26 ( 01 ): 16 ‐ 23.
dc.identifier.citedreferenceAdriaans P. Learning as data compression. In: Conference on Computability in Europe. Berlin, Heidelberg: Springer; 2007: 11 ‐ 24.
dc.identifier.citedreferenceLehmann HP, Downs SM. Desiderata for sharable computable biomedical knowledge for learning health systems. Learning Health Syst. 2018; 2 ( 4 ): e10065.
dc.identifier.citedreferenceSchneeweiss S. Learning from big health care data. N Engl J Med. 2014; 370 ( 23 ): 2161 ‐ 2163.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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