Optum Services (Ireland) Limited

Optum, Inc.

Mostafa Bayomi

Ahmed Selim

Kieran O'Donoghue

Michael Bridges

Neill Michael Byrne

Michael J McCarthy

Gregory J Boss

Vijay S Nori

Rama S Ravindranathan

Systems and methods are disclosed for processing forms to automatically adjudicate religious exemptions. The method includes receiving an input from a user to data fields of forms associated with a religious exemption request, wherein the input is in a first data format and includes location information, religious information, employment information, or demographic information associated with the user. Exemption-relevant features are determined from the input. A data object including the exemption-relevant features is generated. The exemption-relevant features are transformed into corresponding embeddings in a second data format, wherein the embeddings represent semantic relations between the exemption-relevant features. The authenticity of the data object is determined based on the embeddings using a classification model that has been trained using a plurality of embeddings representative of a plurality of exemption-relevant features. A notification is transmitted indicating an approval or a disapproval of the religious exemption request.

Systems and methods for processing forms for automated adjudication of religious exemptions

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis using semi-structured input data. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis using semi-structured input data using at least one of techniques using inferred codified fields and temporally-arranged codified fields.

Machine learning techniques for generating disease prediction utilizing cross-temporal semi-structured input data

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing natural language processing operations using a multi-context convolutional self-attention machine learning framework that comprises a shared token embedding machine learning model, a plurality of context-specific self-attention machine learning models, and a cross-context representation inference machine learning model, where each context-specific self-attention machine learning model is configured to generate, for each input text token of an input text sequence, a context-specific token representation using a context-specific self-attention mechanism that is associated with the respective distinct context window size for the context-specific self-attention machine learning model.

Natural language processing techniques using multi-context self-attention machine learning frameworks

A method comprises: obtaining a current initial image generated by an image generator of an imaging device based on current input signals of sensors of the imaging device; and applying a transformation model to the current initial image to generate a current transformed image, wherein the transformation model is a machine-learning model that has been trained to generate transformed images that more closely resemble reference images generated by a reference image generator.

Enhanced calibration of imaging device output

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing natural language processing (NLP) operations on multi-segment documents. For example, certain embodiments of the present invention utilize systems, methods, and computer program products that perform NLP operations on multi-segment documents by generating document segmentation machine learning models, using document segmentation machine learning models to determine document segments of input multi-segment documents, enabling adaptive multi-segment summarization of multi-segment documents, and enabling guided interaction with multi-segment documents.

Natural language processing operations performed on multi-segment documents

There is a need for more effective and efficient predictive data analysis solutions and/or more effective and efficient solutions for generating image representations of categorical data. In one example, embodiments comprise receiving a categorical input feature, generating an image representation of the categorical input feature, generating an image-based prediction based at least in part on the image representation, and performing one or more prediction-based actions based at least in part on the image-based prediction.

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Dublin, Ireland

Mostafa Bayomi