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公开(公告)号：US12033731B2
公开(公告)日：2024-07-09
申请号：US17168745
申请日：2021-02-05
发明人： Logan R. Meltabarger , Pritesh J. Shah , Amit K. Bothra , David A. Tomala , Christopher R. Markson , Bose S. Daggubati , Christopher G. Lehmuth
CPC分类号： G16H10/60
摘要： A content analysis system includes a processor executing instructions from memory. The instructions include, in response to receiving a request signal from a user device, obtaining feedback items, each having a source indicator; identifying unique source indicators; and, for each source indicator, aggregating corresponding ones of the feedback items. A set of filtered feedback items is generated according to either first or second access levels associated with a user of the user device. A subset of filtered feedback items is selected according to a date range specified by the request signal, a set of automated rules is applied, and natural language processing is performed based on frequency of presence of salient terms to identify themes. A control signal is transmitted to a user interface of the user device instructing display of a representation that indicates a change in the frequency of the identified themes over the specified date range.
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公开(公告)号：US20230274845A1
公开(公告)日：2023-08-31
申请号：US18144330
申请日：2023-05-08
摘要： A method includes receiving historical data collected from a client associated with members. The historical data includes per-member metrics for the client and demographic information for the members. The method includes identifying therapeutic classes for the client based on the per-member metrics and the demographic information. The method includes segmenting the historical data into a data set for each therapeutic class. The method includes, for each therapeutic class of the set of therapeutic classes, determining a pattern for the per-member metrics corresponding to the respective therapeutic class, generating a respective predictive model based on the pattern, and training a neural network of the respective predictive model using a two-stage training process. The predictive model is configured to generate, as output for the therapeutic class, a per-member metric prediction for an input period of future time. The method includes generating predictions for the therapeutic classes using the predictive models.
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公开(公告)号：US11551820B1
公开(公告)日：2023-01-10
申请号：US16731378
申请日：2019-12-31
摘要： A method includes generating an intervention model for a population of users based on contact data, demographic data, and engagement data indicating successfulness of prior interventions for each of the population of users. The method includes, obtaining first data related to a first user, including engagement data indicating successfulness of prior interventions with the first user. The method includes supplying the obtained data as input to the intervention model to determine an intervention expectation, which indicates a likelihood that the first user will take action in response to an intervention. The method includes determining a likelihood of a gap in care. The method includes, in response to the care gap likelihood exceeding a minimum threshold, selecting and scheduling execution of a first intervention. The first intervention is one of a real-time communication with the first user by a specialist and an automated transmission of a message to the first user.
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公开(公告)号：US20210158919A1
公开(公告)日：2021-05-27
申请号：US17168745
申请日：2021-02-05
发明人： Logan R. Meltabarger , Pritesh J. Shah , Amit K. Bothra , David A. Tomala , Christopher R. Markson , Bose S. Daggubati , Christopher G. Lehmuth
IPC分类号： G16H10/60
摘要： A content analysis system includes a processor executing instructions from memory. The instructions include, in response to receiving a request signal from a user device, obtaining feedback items, each having a source indicator; identifying unique source indicators; and, for each source indicator, aggregating corresponding ones of the feedback items. A set of filtered feedback items is generated according to either first or second access levels associated with a user of the user device. A subset of filtered feedback items is selected according to a date range specified by the request signal, a set of automated rules is applied, and natural language processing is performed based on frequency of presence of salient terms to identify themes. A control signal is transmitted to a user interface of the user device instructing display of a representation that indicates a change in the frequency of the identified themes over the specified date range.
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公开(公告)号：US12125598B2
公开(公告)日：2024-10-22
申请号：US18144330
申请日：2023-05-08
摘要： A method includes receiving historical data collected from a client associated with members. The historical data includes per-member metrics for the client and demographic information for the members. The method includes identifying therapeutic classes for the client based on the per-member metrics and the demographic information. The method includes segmenting the historical data into a data set for each therapeutic class. The method includes, for each therapeutic class of the set of therapeutic classes, determining a pattern for the per-member metrics corresponding to the respective therapeutic class, generating a respective predictive model based on the pattern, and training a neural network of the respective predictive model using a two-stage training process. The predictive model is configured to generate, as output for the therapeutic class, a per-member metric prediction for an input period of future time. The method includes generating predictions for the therapeutic classes using the predictive models.
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公开(公告)号：US11379979B2
公开(公告)日：2022-07-05
申请号：US16998358
申请日：2020-08-20
摘要： A computer system includes an input configured to receive a first image of medication located in a receptacle, memory, and a processor configured to execute instructions including creating a second image based on the first image, dividing pixels of the second image into first and second subsets, and scanning the second image along a first axis to count, for each point along the first axis, a number of pixels in the first subset along a line perpendicular to the first axis that intersects the first axis at the point. The instructions also include estimating positions of first and second edges of the receptacle along the first axis based on the counts of the pixels, defining an opening of the receptacle based on the estimated positions of the first and second edges, and outputting a processed image that indicates areas of the image that are outside of the defined opening.
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公开(公告)号：US11361381B1
公开(公告)日：2022-06-14
申请号：US15999135
申请日：2018-08-17
摘要： Data threat evaluation systems and methods are described. A data model structure includes a data subset from the plurality of data types that predate a known threat; this third data subset includes data types from both a first data subset and a second data subset. A model schema extracts, from the data subset, data types of the first subset that predicate and indicate the threat, the model schema to produce at least an individualized data threat regression model, a script originator regression model, and a script filler data threat regression model using the extracted data types. The system may use the models back on the data set to identify potential threats. The system can operate to integrate data to predict fraud, waste or abuse.
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公开(公告)号：US10896048B1
公开(公告)日：2021-01-19
申请号：US16117140
申请日：2018-08-30
IPC分类号： G06F7/02 , G06F16/00 , G06F9/451 , G16H40/67 , G06F17/11 , G06Q10/08 , G16H70/40 , G06N20/00
摘要： A computer system for dynamic adaptation of a user interface according to data store mining includes a data store configured to index event data of a plurality of events. A data analyst device is configured to render the user interface to a data analyst and transmit a message that identifies a selected identifier of the plurality of identifiers. A data processing circuit is configured to train a machine learning model based on event data stored by the data store for a first set of identifiers from within a predetermined epoch. An interface circuit determines an interface metric for the selected identifier based on the determined output of the selected identifier and transmits the interface metric to the data analyst device. The data analyst device is configured to, in response to the interface metric from the interface circuit, selectively perform a modification or removal of a second user interface element.
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公开(公告)号：US10776916B2
公开(公告)日：2020-09-15
申请号：US16190548
申请日：2018-11-14
摘要： A method includes capturing a first image of medication held by a receptacle. The method includes creating a second image based on the first image. The method includes determining a first subset of pixels of the second image that are more likely to correspond to the receptacle. The method includes processing the second image along a first axis by, for each point: defining a line perpendicularly intersecting the first axis at the point and counting how many of the pixels located along the line are in the first subset. The method includes determining first and second local maxima of the counts. The method includes estimating positions of first and second edges of the receptacle based on positions of the local maxima. The method includes defining an ellipse based on the first and second edges and excluding areas of the first image outside the defined ellipse from further processing.
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公开(公告)号：US11830610B2
公开(公告)日：2023-11-28
申请号：US18092260
申请日：2022-12-31
IPC分类号： G16H40/20 , G06N3/08 , G06Q50/00 , G06Q30/0201 , G06Q10/107 , G16H20/10 , G16H50/30 , G16H50/20 , G16H50/70 , A61B5/00 , G16H80/00 , H04L65/1066
CPC分类号： G16H40/20 , A61B5/4833 , G06N3/08 , G06Q10/107 , G06Q30/0201 , G06Q50/01 , G16H20/10 , G16H50/20 , G16H50/30 , G16H50/70 , G16H80/00 , H04L65/1066
摘要： A method includes generating an intervention model by determining principal components for features of a training set, associating each feature of the training set with a principal component, selecting features of the training set most highly correlated with principal components, training a machine learning model with at least some of the selected features, and saving the verified trained machine learning model as the intervention model. The method includes determining multiple channel-specific intervention expectations. Each channel-specific intervention expectation indicates a likelihood that the user will take action in response to an intervention being executed using the engagement channel corresponding to the channel-specific intervention expectation. The method includes selecting an intervention and scheduling the selected intervention for execution.
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