http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11222721-B2

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classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q50-22
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filingDate 2019-05-03^^<http://www.w3.org/2001/XMLSchema#date>
grantDate 2022-01-11^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_00eb495bf14ed6083621228e1b5ae0c3
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publicationDate 2022-01-11^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber US-11222721-B2
titleOfInvention Peer community based anomalous behavior detection
abstract A peer network may include nodes corresponding to different clinicians. An edge may interconnect the two nodes based on the corresponding clinicians sharing at least one common attribute such as for example, treating the same patients and/or interacting with the same medical devices. A machine-learning model may be applied to identify, in the peer network, one or more peer communities of clinicians. The activity pattern of a clinician may be compared to the activity patterns of other clinicians in the same peer community to determine whether that clinician exhibits anomalous behavior. An investigative workflow may be triggered when the clinician is determined to exhibit anomalous behavior. The investigative workflow may include generating an alert, activating surveillance devices, and/or isolating medication accessed by the clinician.
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