Optum Services (ireland) Limited

Harutyun Shahumyan

Hendrik Kleine

Vicente Rubén Del Pino Ruiz

Karim Mahmoud Mohamed Moustafa

Kieran O'Donoghue

Neill Michael Byrne

Michael J McCarthy

David Lewis Frankenfield

Lisa E Walsh

Gevorg Poghosyan

Kieran M Cooney

Solutions for more efficient and effective traversal of infection networks are disclosed. In one example, a method includes identifying a plurality of candidate traversal paths for the traversal agent object; for each candidate traversal path of the plurality of candidate traversal paths, determining a cross-node infectious encounter profile that defines one or more predicted infectious encounters for the traversal agent data object, determining a predicted total viral particle inhalation (VPI) measure for each predicted infectious encounter of the one or more predicted infectious encounters, and determining a path risk score based at least in part on each predicted total VPI measure for a predicted infectious encounter of the one or more predicted infectious encounters; determining the optimal traversal path based at least in part on each path risk score for a candidate traversal path of the plurality of candidate traversal paths; and performing one or more prediction-based actions based at least in part on the optimal traversal path.

Predictive data analysis techniques for optimal traversal of infection networks

Various embodiments provide methods, apparatus, systems, computing entities, and/or the like, for performing predictive recommendation. In one example embodiment, a method is provided. The method includes generating guideline data objects for a plurality of service need conditions. The method includes generating a compliance profile data object for each of a plurality of provider entities. The compliance profile data object for a provider entity includes compliance scores with respect to the plurality of service need conditions, a compliance score determined using procedural record data objects associated with each provider entity and the guideline data objects. The method further includes selecting a subset of the plurality of provider entities according to the compliance profile data object for each provider entity. The method further includes performing at least one automated recommendation-based action based at least in part on the selected subset.

Predictive recommendation systems using compliance profile data objects

Various embodiments of the present invention introduce techniques for efficient and resilient network-wide supervision of a hierarchically-segmented blockchain network. A hierarchically-segmented blockchain network may include S segment ledger systems associated with S network segments and G local ledger systems. In response, various embodiments of the present invention utilize a centralized global ledger monitoring system that non-persistently monitors the S+G monitored systems via periodic chaincodes that are configured to verify targeted transactions associated with particular local ledgers and/or segment-wise ledgers during particular transactional junctures associated with ledger data. In this way, by enabling targeted monitoring of a hierarchically-segmented blockchain network using a centralized global ledger monitoring system that non-persistently monitors the monitored systems via periodic chaincodes that are configured to verify targeted transactions in particular transactional junctures, various embodiments of the present invention introduce techniques for efficient and resilient network-wide supervision of a hierarchically-segmented blockchain network.

Network-wide supervision in a hierarchically-segmented blockchain network

In general, this disclosure describes techniques for automatically restructuring a database to improve one or more parameters of the database. In some examples, a computing system is configured to extract a set of columns and merge the set of columns into a new table of a first new candidate model of the database; determine a table of the database based on a number of columns of that are involved in query 'where' or “join” clauses; merge the table with one or more connected tables in a second new candidate model of the database, wherein the one or more connected tables are connected to the table by at least one of the “where” or “join” clauses; select a model of the database from among the candidate models based on one or more parameters; and use the selected model as the current model of the database.

Automated database modeling

There is a need for solutions for more efficient predictive data analysis systems. This need can be addressed, for example, by a system configured to receive temporal inferences for a predictive task, where each temporal inference is associated with a temporal benchmark and the temporal benchmarks include a base temporal benchmark and supplemental temporal benchmarks; generate a cross-temporal prediction for the predictive task by applying one or more cross-temporal probabilistic updates to the base temporal inference, where each cross-temporal probabilistic update is associated with a supplemental temporal benchmark; and display the cross-temporal prediction using a cross-temporal prediction interface.

Growing community of inventors

Dublin, Ireland

Harutyun Shahumyan