Patents by Inventor Michael Byrne

Michael Byrne has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250132062
    Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for generating a correlated prediction for an input data record by generating a correlation matrix based on co-occurrences associated with a plurality of reference non-correlated predictions, generating a simulation matrix comprising a plurality of simulation data records based on a number of simulation instances and the plurality of reference non-correlated predictions, generating a plurality of correlated simulation data records based on the correlation matrix and select ones of the plurality of simulation data records, generating one or more univariates based on the plurality of correlated simulation data records, and determining a correlated prediction based on a comparison of the one or more univariates and a plurality of input non-correlated probabilities associated with the input data record.
    Type: Application
    Filed: January 4, 2024
    Publication date: April 24, 2025
    Inventors: Michael J. McCarthy, Neill Michael Byrne
  • Patent number: 12229188
    Abstract: 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.
    Type: Grant
    Filed: May 17, 2022
    Date of Patent: February 18, 2025
    Assignee: Optum Services (Ireland) Limited
    Inventors: Michael J. McCarthy, Kieran O'Donoghue, Mostafa Bayomi, Neill Michael Byrne, Vijay S. Nori
  • Patent number: 12159409
    Abstract: 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.
    Type: Grant
    Filed: April 21, 2022
    Date of Patent: December 3, 2024
    Assignee: Optum Services (Ireland) Limited
    Inventors: Kieran O'Donoghue, Mostafa Bayomi, Neill Michael Byrne, Michael J McCarthy, Ahmed Selim
  • Publication number: 20240378561
    Abstract: Apparatus and methods for managing disciplinary policies are described herein. In some embodiments, a processor may receive a disciplinary policy and an infraction record. In some embodiments, a processor may determine a resolution datum request, transmit it to a user, and receive a resolution datum. In some embodiments, a processor may communicate an infraction notice to a user and receive a response.
    Type: Application
    Filed: May 8, 2023
    Publication date: November 14, 2024
    Applicant: CropGuidance, LLC
    Inventor: Michael Byrne
  • Publication number: 20240240666
    Abstract: An expandable washer includes a first washer piece comprising a first plurality of steps arranged about a first helical ramp, and a second washer piece comprising a second plurality of steps arranged about a second helical ramp and configured so that at least one step of the second plurality of steps matingly abuts at least one step of the first plurality of steps when the second washer piece is inserted into the first washer piece.
    Type: Application
    Filed: January 12, 2024
    Publication date: July 18, 2024
    Inventors: Christopher Steven Adams, Donny Michael Byrne
  • Publication number: 20240231897
    Abstract: Server instantiation or deployment with at least an orchestrated post-deployment configuration service utilizing an exemplary framework providing script orchestration, logging, retry logic and environment-specific infrastructure and service configurations. At least one repository may store configuration scripts (or their equivalent), including first scripts associated with, e.g., a multi-tenant system, vendor, database provider, controller, etc., and second scripts associated with, e.g., a tenant, a database client, customer, etc. After instantiating or installing a server, it may be configured with orchestrated execution to ensure successful first server configuration, and then further configured with orchestrated execution of second scripts to ensure successful subsequent server configuration. Orchestration includes retry logic, logging, and reboot support to repeat or continue script execution after reboot, and the number of scripts series is arbitrary, e.g., there may first, second, third, etc.
    Type: Application
    Filed: January 9, 2023
    Publication date: July 11, 2024
    Applicant: Salesforce, Inc.
    Inventors: Raffaele Vigliotti, Sze K. Li, Oleksandr Senyuk, Michael Byrne, Omar Jaber, Bradley Kenneth Michel
  • Patent number: 12033367
    Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.
    Type: Grant
    Filed: August 29, 2023
    Date of Patent: July 9, 2024
    Assignee: Bank of America Corporation
    Inventors: Van Nguyen, Sean Michael Byrne, Syed Talha, Aftab Khan, Beena Khushalani, Sharad K. Kalyani
  • Publication number: 20240185352
    Abstract: Various embodiments of the present disclosure describe simulation, prediction, and data augmentation techniques for intelligently evaluating predictive risk scores and/or one or more combinations thereof. The techniques include generating, using a risk prediction model, predictive risk scores for an agent dataset. The techniques include generating simulated risk scores for the agent dataset based on the predictive risk scores and a first performance metric for the risk prediction model. The techniques include generating refined risk scores for the agent dataset based on the simulated risk scores and a second performance metric for a target risk refinement model. The techniques include generating return metrics for the target risk refinement model based on one or more iterations of an agent-based simulation enabled by the predictive risk scores, simulated risk scores, and refined risk scores.
    Type: Application
    Filed: February 3, 2023
    Publication date: June 6, 2024
    Inventor: Neill Michael Byrne
  • Publication number: 20240075939
    Abstract: Raw sensor data from a device of a user is collected. The raw data does not include location data for the device. The data is preprocessed to identify driving trips in which the user had the device. The trip data is provided to machine-learning models (MLMs) as input and the MLMs provide as output predictions for each trip's estimated speeds, estimated number of hard brakes and a degree of each hard brake, and estimated degrees of distracted driving. A duration, time of day, and calendar date of each trip is identified. The predictions, duration, time of day, and calendar date are modified into four factor values. The four modified factor values are combined into an overall driver characteristic value and provided to a network service associated with the user for purposes of providing or modifying services provided to the user through the network service based on the overall characteristic value.
    Type: Application
    Filed: September 2, 2022
    Publication date: March 7, 2024
    Inventors: Kyle Patrick Schmitt, Cheng Li, Evan Michael Byrne, Scott David Huber, Kyle Jacob Parsons
  • Publication number: 20230410462
    Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.
    Type: Application
    Filed: August 29, 2023
    Publication date: December 21, 2023
    Inventors: Van Nguyen, Sean Michael Byrne, Syed Talha, Aftab Khan, Beena Khushalani, Sharad K. Kalyani
  • Patent number: 11842263
    Abstract: There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing cross-temporal predictive data analysis. In one example, a method includes determining a time-adjusted encoding for each temporal unit of a group of temporal units, processing each time-adjusted encoding using a cross-temporal encoding machine learning model to generate a cross-temporal encoding of the group of temporal units, and performing one or more prediction-based actions based at least in part on the cross-temporal encoding.
    Type: Grant
    Filed: June 11, 2020
    Date of Patent: December 12, 2023
    Assignee: Optum Services (Ireland) Limited
    Inventors: Neill Michael Byrne, Michael J. McCarthy, Kieran O'Donoghue
  • Publication number: 20230394352
    Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for converting a multilabel classification model into a sequence of a plurality of binary classification models based on a plurality of label subgroups associated with the multilabel classification model, where the label subgroups comprise an optimal subgroup size, the optimal subgroup size is generated by optimizing an optimization measure defined by a subgroup size variable and a total inner group correlation measure, and identifying label membership to a particular subgroup by using a mixed integer linear program model.
    Type: Application
    Filed: June 7, 2022
    Publication date: December 7, 2023
    Inventors: Neill Michael Byrne, Kieran O'Donoghue, Michael J. McCarthy
  • Publication number: 20230376532
    Abstract: 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.
    Type: Application
    Filed: May 17, 2022
    Publication date: November 23, 2023
    Inventors: Michael J. McCarthy, Kieran O'Donoghue, Mostafa Bayomi, Neill Michael Byrne, Vijay S. Nori
  • Publication number: 20230342932
    Abstract: 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.
    Type: Application
    Filed: April 21, 2022
    Publication date: October 26, 2023
    Inventors: Kieran O'Donoghue, Mostafa Bayomi, Neill Michael Byrne, Michael J. McCarthy, Ahmed Selim
  • Patent number: 11798258
    Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The text includes errors associated with noise in the image. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the errors from the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.
    Type: Grant
    Filed: May 3, 2021
    Date of Patent: October 24, 2023
    Assignee: Bank of America Corporation
    Inventors: Van Nguyen, Sean Michael Byrne, Syed Talha, Aftab Khan, Beena Khushalani, Sharad K. Kalyani
  • Patent number: 11797354
    Abstract: There is a need for more effective and efficient constrained-optimization-based operational load balancing. In one example, a method comprises determining constraint-satisfying operator-unit mapping arrangements that satisfy an operator unity constraint and an operator capacity constraint; for each constraint-satisfying operator-unit mapping arrangement, determining an arrangement utility measure; processing each arrangement utility measure using an optimization-based ensemble machine learning model that is configured to determine an optimal operator-unit mapping arrangement of the plurality of constraint-satisfying operator-unit mapping arrangements; and initiating the performance of one or more operational load balancing operations based on the optimal operator-unit mapping arrangement.
    Type: Grant
    Filed: October 21, 2022
    Date of Patent: October 24, 2023
    Assignee: Optum Services (Ireland) Limited
    Inventors: Kieran O'Donoghue, Michael J. McCarthy, Neill Michael Byrne, David Lewis Frankenfield
  • Patent number: 11704352
    Abstract: An apparatus includes a memory and processor. The memory stores OCR and NLP algorithms. The processor receives an image of a physical document page and executes the OCR algorithm to convert the image into text. The processor identifies errors in the text, which are associated with noise in the image. The processor generates a feature vector that includes features obtained by executing the NLP algorithm on the text, and features associated with the identified errors in the text. The processor uses the feature vector to assign the image to a document category. Documents assigned to the document category share one or more characteristics, and the feature vector is associated with a probability greater than a threshold that the physical document associated with the image includes those characteristics. The processor then stores the image in a database as a page of an electronic document belonging to the assigned document category.
    Type: Grant
    Filed: May 3, 2021
    Date of Patent: July 18, 2023
    Assignee: Bank of America Corporation
    Inventors: Van Nguyen, Sean Michael Byrne, Syed Talha, Aftab Khan, Beena Khushalani, Sharad K. Kalyani
  • Patent number: 11645565
    Abstract: 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.
    Type: Grant
    Filed: November 12, 2019
    Date of Patent: May 9, 2023
    Assignee: Optum Services (Ireland) Limited
    Inventors: Michael J. McCarthy, Kieran O'Donoghue, Harutyun Shahumyan, Neill Michael Byrne, David Lewis Frankenfield
  • Publication number: 20230122121
    Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for perform predictive data analysis operations. For example, certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis operations by using a cross-temporal encoding machine learning model, such as a cross-temporal encoding machine learning model that is generated by using a target intervention classification machine learning model to map outputs of the cross-temporal encoding machine learning model to historical target intervention labels, thus enabling supervised training of the cross-temporal encoding machine learning without the need for ground-truth data corresponding to the output of the cross-temporal encoding machine learning model.
    Type: Application
    Filed: October 18, 2021
    Publication date: April 20, 2023
    Inventors: Kieran O'Donoghue, Neill Michael Byrne, Michael J. McCarthy
  • Publication number: 20230075176
    Abstract: Various embodiments provide methods, apparatus, systems, computing entities, and/or the like, providing a temporal disease risk profile describing a likelihood of disease onset over time for an individual in a dynamically interpretable manner. Interpretability of the temporal disease risk profile is enabled by providing additional and contextual information, such as weight distributions of various health indicators, factors, and features.
    Type: Application
    Filed: September 8, 2021
    Publication date: March 9, 2023
    Inventors: Michael J. McCarthy, Kieran O'Donoghue, Neill Michael Byrne