Zengine Limited

Stephen Brobst

Michael B McDonald

Michael P Sheehan

John Trustman

A system for selection of a medical provider (MP) by a requesting patient based on preferences for the MP includes a first model modeling the preferences of a plurality of patients for select MPs and trained on a first training data set. A second model is provided for modeling the preferences of a plurality of MPs for select patients and trained on a second training data set. A controller controls the first and second models to select at least a portion of available MPs in an available MP data set for input of the associated representative information to the first and second model MP inputs. A patient rank calculator accumulates the output patient determined preferences for MPs associated with the selected at least a portion of the available MPs and generates a MP ranking for each of the selected at least a portion of the available MPs. An MP rank calculator accumulates the output MP determined preferences for the requesting patient for each of the selected at least a portion of the available MPs and generates a patient ranking for each of the selected at least a portion of the available MPs. A plurality of weighting blocks are associated with at least one of the patient rank calculator and the MP rank calculator and with a determined preference of a rank calculator. A control input to each of the plurality of weighting blocks controls a weighting value applied by the plurality of weighting blocks to each of the associated determined preferences. A modifier modifies the patient ranking output of the patient rank calculator with the output of the MP rank calculator to provide as an output in response to the query from the requesting patient a resultant ranking list for each of the selected at least a portion of the available MPs.

Machine learning system for asymmetrical matching of care givers and care receivers

A system for selection of a medical provider (MP) by a requesting patient based on preferences for the MP includes a first model modeling the preferences of a plurality of patients for select MPs and trained on a first training data set comprised of patients and MPs. The patients in the first training data set have rated at least one of the MPs in the first data set by a predetermined set of patient determined preferences. A second model is provided for modeling the preferences of a plurality of MPs for select patients and trained on a second training data set comprised of MPs and patients. The MPs in the second training data set have rated at least one of the patients in the second data set by a predetermined set of MP determined preferences. An available MP data set is provided containing information representative of available MPs for selection thereof by the requesting patient. A controller controls the first and second models to select at least a portion of the available MPs in the available MP data set for input of the associated representative information to the first and second model MP inputs. A list generator generates a ranked list of available MPs from the output of the first model for the requesting patient. A combiner modifies the ranked list of available MPs by the output of the second model to output a modified ranked list.

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Las Vegas, NV, United States of America

Stephen Brobst