Optum, Inc.

Adam Russell

Robert Kahn Rossmiller

Vijay S Nori

Vezly Gracies

Sushma Ambati

Gregory J Boss

Damian Kelly

Daniel J Mulcahy

Paul Bleicher

Ayush Tomar

Ramprasad Anandam Gaddam

Somadev Pasala

Ramin Anushiravani

Ravi Kondadadi

Sanjeeva L Fernando

Hadi D Halim

Subhash Seelam

Donald E Johnson, Jr

Robert K Rossmiller

Kemeng Li

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for processing an inclusion of an entity for an event. In accordance with one embodiment, a method is provided that includes: determining whether a graph representation data object comprises an inbound edge connecting an entity node representing the entity with an event node representing the event; and responsive to determining the graph representation data object comprises the inbound edge, performing an action involving inclusion of the entity for the event. The inbound edge is generated via an inbound edge generator machine learning model configured to: traverse entity and/or inclusion edges of the graph representation data object to identify inclusion and entity edges connected, generate an entity score data object for the entity based at least in part on the inclusion edges, and responsive to the data object satisfying a threshold, generate the inbound edge.

Graph data representation systems and methods for eligibility determination and/or monitoring

Various embodiments of the present disclosure provide automated data compliance techniques for complex access controlled datasets subject to a plurality of data access constraints. Some of the techniques may include generating, using one or more natural language models, entity-relationship data for an access controlled dataset and generating a knowledge graph based on the entity-relationship data. The knowledge graph includes a plurality of vertices connected by a plurality of edges that may be traversed to identify a data access condition indicative of a data access violation or a data coverage violation. Some of the techniques may include generating, using the knowledge graph, a natural language condition description based on the data access condition and providing a condition alert indicative of the natural language condition description.

Graph-based data compliance using natural language text

There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing/executing hybrid input predictive data analysis. In one example, a method includes identifying a vocabulary data object associated with one or more prediction input text data objects; determining, based at least in part on the vocabulary data object, a per-input-entity tokenized representation for the one or more prediction input text data objects; determining, based at least in part on the per-input-entity tokenized representation and one or more prediction input structured data objects and using a hybrid-input predictive model, a prediction score; determining, based at least in part on one or more threshold determination configuration criteria, a predictive threshold for the hybrid-input predictive model; generating, based at least in part on the prediction score and the predictive threshold, a predictive output; and performing one or more prediction-based actions based at least in part on the predictive output.

Hybrid-input predictive data analysis

Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for multi-node system monitoring using one or more distributed ledgers, wherein a ledger entry request received from a miner node computing entity is validated based at least in part on executing a hierarchical validation workflow that comprises an ordered sequence of L validation iterations, wherein each of one or more ith non-initial validation iterations is performed based at least in part on an association of an (i−1)th validation iteration with a non-affirmative validation determination.

Monitoring a distributed ledger network using hierarchical validation workflows

An analytics platform and architecture is disclosed that improves the capture, extraction, and reporting of data required for certain measures, provides real-time data surveillance, dashboards, tracking lists, and alerts for specific, high-priority data, and offers dynamic, ad-hoc reporting capabilities. The platform includes a data extraction facility that gathers data from numerous sources, a data mapping facility that identifies and maps key data elements and links data over time, a data normalization facility to normalize the data and, optionally, de-identify the data, a flexible data warehouse for storing raw data or longitudinal data, an analytics facility for data mining, analytic model building, risk identification, benchmarking and tracking. The improved platform and architecture integrates social networking technology and analysis (SNA) on data to cluster data for more efficient, technically improved and focused processing.

Data processing systems and methods implementing improved analytics platform and networked information systems

Growing community of inventors

Arlington, MA, United States of America

Adam Russell