Abstract: An association metric for record attributes associated with cardinalities that are not necessarily the same is used for training and/or applying an entity resolution (ER) model. A pair of records includes (a) a first record indicating a first set of values for a first attribute and (b) a second record indicating a second set of values for a second attribute. Each of the first set of values and each of the second set of values are compared to determine individual association metrics. A first-level reduction operation is applied to subsets of the individual association metrics to determine reduced association metrics. A second-level reduction operation is applied to the reduced association metrics to determine an association metric, for the pair of records, for training and/or applying an ER model.
Type:
Grant
Filed:
May 8, 2019
Date of Patent:
February 27, 2024
Assignee:
KOMODO HEALTH
Inventors:
Benjamin James Campbell Blalock, Alexander Graham Glenday, Jason Richard Prestinario
Abstract: An association metric for record attributes associated with cardinalities that are not necessarily the same is used for training and/or applying an entity resolution (ER) model. A pair of records includes (a) a first record indicating a first set of values for a first attribute and (b) a second record indicating a second set of values for a second attribute. Each of the first set of values and each of the second set of values are compared to determine individual association metrics. A first-level reduction operation is applied to subsets of the individual association metrics to determine reduced association metrics. A second-level reduction operation is applied to the reduced association metrics to determine an association metric, for the pair of records, for training and/or applying an ER model.
Type:
Application
Filed:
May 8, 2019
Publication date:
November 12, 2020
Applicant:
KOMODO HEALTH
Inventors:
Benjamin James Campbell Blalock, Alexander Graham Glenday, Jason Richard Prestinario
Abstract: Techniques for generating and presenting graph data structures representing patient visit paths and physician referral networks are disclosed. A system generates one or more graph data structures representing one or more referred visit paths and/or inferred visit paths. Based on the graph data structures representing the visit paths, the system generates another graph data structure representing a physician network. A user interface presents a graph representing the physician network. Based on the presented graph, a user may thereby determine influential levels of different physicians for referring one or more patients to a particular physician.
Type:
Application
Filed:
May 8, 2019
Publication date:
November 12, 2020
Applicant:
KOMODO HEALTH
Inventors:
Benjamin James Campbell Blalock, Alexander Graham Glenday, Jason Richard Prestinario