Dynamic user interface generation for delivery scheduling optimization

    公开(公告)号:US12087420B2

    公开(公告)日:2024-09-10

    申请号:US17994609

    申请日:2022-11-28

    CPC classification number: G16H20/10 G06Q10/083 G06Q10/1097

    Abstract: A system for generating dynamic user interfaces includes memory hardware storing instructions and processor hardware executing the instructions. The instructions include generating an interactive graphical user interface with fields corresponding to dates. The instructions include generating a selectable user interface element at a first field corresponding to a scheduled delivery date for a recipient. The instructions include, in response to a user dragging-and-dropping the selectable user interface element to a second field corresponding to an adjusted delivery date for the recipient, calculating a supply measure of a prior fill remaining with the recipient based on a stated duration of the prior fill and a date indicating receipt of the prior fill by the recipient. The instructions include, in response to the supply measure being greater than the threshold, moving the selectable user interface element to the second field and updating the scheduled delivery date to be the adjusted delivery date.

    TREE BASED DETECTION OF DIFFERENCES IN DATA
    112.
    发明公开

    公开(公告)号:US20240296154A1

    公开(公告)日:2024-09-05

    申请号:US18117054

    申请日:2023-03-03

    Abstract: Methods and systems are provided for performing operations comprising: accessing, by one or more processors, a first set of data from a first source and a second set of data from a second source; extracting, based on a key, a first subset of data from the first set of data and a second subset of data from the second set of data; generating a first Merkle tree based on the first subset of data and a second Merkle tree based on the second subset of data; comparing a first node from the first Merkle tree with a corresponding second node from the second Merkle tree; and identifying one or more differences between the first subset of data and the second subset of data in response to determining that the first node fails to match the second node.

    Alternate dose regimen identification system

    公开(公告)号:US12073931B2

    公开(公告)日:2024-08-27

    申请号:US17841320

    申请日:2022-06-15

    CPC classification number: G16H20/10 G16H40/20

    Abstract: Methods and systems for performing dose regimen modification are provided. The methods and systems perform operations comprising: receiving prescription related data for treating a patient with an expected level of efficacy, the prescription related data comprising medication regimen information including dose and interval; determining, using a model, a first amount of drug waste based on the prescription related data; comparing the first amount of drug waste to a threshold value; and in response to determining that the first amount of drug waste transgresses the threshold value, identifying an alternate medication regimen that is associated with a treatment having a given level of efficacy corresponding to the expected level of efficacy, the alternate medication regimen being associated with a second amount of drug waste that is lower than the first amount of drug waste; and triggering a notification associated with the alternate medication regimen.

    Methods and systems for maintaining pharmacy provider networks

    公开(公告)号:US12039608B2

    公开(公告)日:2024-07-16

    申请号:US17405818

    申请日:2021-08-18

    CPC classification number: G06Q40/08 G06Q50/22

    Abstract: Methods and systems for maintaining pharmacy provider networks are described. In one embodiment, claims adjudication data associated with a member and a prescribed drug is accessed. The prescribed drug associated with the member is classified as one of an acute medication and a maintenance medication. A pharmacy provider network is associated with the prescribed drug based on, at least in part, classifying the prescribed drug. It is determined if a pharmacy associated with the claims adjudication data is included within the pharmacy provider network associated with the prescribed drug. A pharmacy claim may be adjudicated for the prescribed drug based on the claim and the pharmacy provider network. Additional methods and systems are disclosed.

    METHODS AND SYSTEMS FOR AUTOMATIC AUTHORIZATION USING MACHINE LEARNING ALGORITHM

    公开(公告)号:US20240203587A1

    公开(公告)日:2024-06-20

    申请号:US18082745

    申请日:2022-12-16

    CPC classification number: G16H50/20 G16H50/70

    Abstract: Methods and systems for selecting a deep learning/machine learning model are described. In one embodiment, a plurality of models are optimized by addressing class imbalances among a first subset of records, each of the plurality of models are trained using the first subset of records, each of the plurality of models are implemented to predict a value of respective known target columns in each of a second subset of records, respective success rates for each of the plurality of models at predicting the respective known target columns for each of the second subset of records are determined, a first of the plurality of models having a highest success rate is selected, and the first of the plurality of models is implemented to decide a target column of a received authorization request based on predictor columns in the received authorization request.

    PREDICTIVE MODELING PROFILE CONFIGURATIONS UNDER CONSTRAINED CONDITIONS

    公开(公告)号:US20240160631A1

    公开(公告)日:2024-05-16

    申请号:US18388905

    申请日:2023-11-13

    CPC classification number: G06F16/2457 G06F16/219

    Abstract: A computerized method includes obtaining a set of historical data characterizing interactions of a user with a first network provider and a second network provider. The first network provider includes a restrictive condition with respect to the second network provider, and the restrictive condition indicates that a network provider preference included in configuration data corresponding to an account of the user is constrained to one of the first network provider or the second network provider. The method includes generating, using the set of historical data, a predicted network provider indicating one of the first network provider or the second network provider. The method includes communicating the predicted network provider as a recommended network provider preference for the configuration data corresponding to the account of the user.

    ITERATED TRAINING OF MACHINE MODELS WITH DEDUPLICATION

    公开(公告)号:US20240120103A1

    公开(公告)日:2024-04-11

    申请号:US18543804

    申请日:2023-12-18

    CPC classification number: G16H50/20 G06N20/00 G06Q50/22 G16H10/60

    Abstract: A computer-implemented method includes defining model attributes including a training iteration value that defines a set of training iterations to be used in machine learning to associate portions of feedback data with a set of topic groups based on similarities in concepts conveyed in the feedback data. The method includes removing at least some of the confidential information from the feedback data. The method includes receiving a topic model number selection that indicates a subset of the set of topic groups. The method includes using machine learning to train a machine model based on the model attributes and the topic model number selection. The method includes generating a display showing at least one of a topic cluster graph or a word cloud based on the machine model.

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