Patents by Inventor Jeffrey D. Larson
Jeffrey D. Larson 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).
-
Patent number: 11763950Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, and more specifically, to computer network architectures in the context of program rules, using combinations of defined patient clinical episode metrics and other clinical metrics, thus enabling superior performance of computer hardware. Aspects of embodiments herein are specific to patient clinical episode definitions, and are applied to the specific outcomes of highest concern to each episode type. Furthermore, aspects of embodiments herein produce more accurate and reliable predictions of possible patient outcomes and metrics.Type: GrantFiled: August 16, 2018Date of Patent: September 19, 2023Assignee: Clarify Health Solutions, Inc.Inventors: Jeffrey D. Larson, Yale Wang, Samuel H. Bauknight, Justin Warner, Todd Gottula, Jean P. Drouin
-
Patent number: 11748820Abstract: Computer network architectures for machine learning, and more specifically, computer network architectures for the automated completion of healthcare claims. Embodiments of the present invention provide computer network architectures for the automated completion of estimated final cost data for claims for healthcare clinical episodes using incomplete data for healthcare insurance claims and costs, known to date. Embodiments may use an automatic claims completion web application, with other computer network architecture components. Embodiments may include a combination of third-party databases to generate estimated final claims for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, social-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: October 22, 2022Date of Patent: September 5, 2023Assignee: Clarify Health Solutions, Inc.Inventors: Jean P. Drouin, Samuel H. Bauknight, Todd Gottula, Yale Wang, Adam F. Rogow, Jeffrey D. Larson, Justin Warner, Erik Talvola
-
Patent number: 11742091Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and active updates of outcomes. Embodiments of computer network architecture automatically update forecasts of outcomes of patient episodes and annual costs for each patient of interest after hospital discharge. Embodiments may generate such updated forecasts either occasionally on demand, or periodically, or as triggered by events such as an update of available data for such forecasts. Embodiments may include a combination of third-party databases to generate the updated forecasts for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: October 22, 2022Date of Patent: August 29, 2023Assignee: Clarify Health Solutions, Inc.Inventors: Todd Gottula, Jean P. Drouin, Yale Wang, Samuel H. Bauknight, Adam F. Rogow, Jeffrey D. Larson, Justin Warner, Erik Talvola
-
Patent number: 11636497Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and risk adjusted performance ranking of healthcare providers. Embodiments of computer network architecture automatically make risk adjusted performance rankings of healthcare service providers and generate and transmit reports of the rankings. Embodiments may generate such rankings either occasionally on demand, or periodically, or as triggered by events such as an update of available data for such forecasts. Embodiments may include a combination of third-party databases to generate the updated forecasts for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: January 27, 2022Date of Patent: April 25, 2023Assignee: Clarify Health Solutions, Inc.Inventors: Erik Talvola, Emmet Sun, Adam F. Rogow, Jeffrey D. Larson, Justin Warner
-
Patent number: 11625789Abstract: Computer network architectures for machine learning, and more specifically, computer network architectures for the automated completion of healthcare claims. Embodiments of the present invention provide computer network architectures for the automated completion of estimated final cost data for claims for healthcare clinical episodes using incomplete data for healthcare insurance claims and costs, known to date. Embodiments may use an automatic claims completion web application, with other computer network architecture components. Embodiments may include a combination of third-party databases to generate estimated final claims for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, social-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: April 2, 2019Date of Patent: April 11, 2023Assignee: Clarify Health Solutions, Inc.Inventors: Jean P. Drouin, Samuel H. Bauknight, Todd Gottula, Yale Wang, Adam F. Rogow, Jeffrey D. Larson, Justin Warner, Erik Talvola
-
Patent number: 11621085Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and active updates of outcomes. Embodiments of computer network architecture automatically update forecasts of outcomes of patient episodes and annual costs for each patient of interest after hospital discharge. Embodiments may generate such updated forecasts either occasionally on demand, or periodically, or as triggered by events such as an update of available data for such forecasts. Embodiments may include a combination of third-party databases to generate the updated forecasts for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: April 18, 2019Date of Patent: April 4, 2023Assignee: CLARIFY HEALTH SOLUTIONS, INC.Inventors: Todd Gottula, Jean P. Drouin, Yale Wang, Samuel H. Bauknight, Adam F. Rogow, Jeffrey D. Larson, Justin Warner, Erik Talvola
-
Patent number: 11605465Abstract: Embodiments relate generally to computer network architectures for machine learning, and more specifically, to computer network architectures in the context of program rules, using combinations of defined patient clinical episode metrics and other clinical metrics, thus enabling superior performance of computer hardware. Aspects of embodiments herein are specific to patient clinical episode definitions, and are applied to the specific outcomes of highest concern to each episode type. Furthermore, aspects of embodiments herein produce more accurate and reliable predictions of possible patient outcomes and metrics.Type: GrantFiled: November 25, 2019Date of Patent: March 14, 2023Assignee: Clarify Health Solutions, Inc.Inventors: Jeffrey D. Larson, Yale Wang, Samuel H. Bauknight, Justin Warner, Todd Gottula, Jean P. Drouin
-
Patent number: 11527313Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and the automatic development of patient care groupings of patient data. Embodiments of computer network architecture automatically generate care grouping, and organize and analyse patient care data accordingly, and generate and transmit reports of the care grouping definitions, data, and analysis. Embodiments may generate care groupings either occasionally on demand, or periodically, or as triggered by events such as an update of available data. Embodiments may include a combination system databases with data provided by system users, and third-party databases to generate the patient care groupings, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: February 22, 2022Date of Patent: December 13, 2022Assignee: Clarify Health Solutions, Inc.Inventors: Erik Talvola, Emmet Sun, Adam F. Rogow, Jeffrey D. Larson, Justin Warner
-
Patent number: 11270785Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and the automatic development of patient care groupings of patient data. Embodiments of computer network architecture automatically generate care grouping, and organize and analyse patient care data accordingly, and generate and transmit reports of the care grouping definitions, data, and analysis. Embodiments may generate care groupings either occasionally on demand, or periodically, or as triggered by events such as an update of available data. Embodiments may include a combination system databases with data provided by system users, and third-party databases to generate the patient care groupings, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: November 27, 2019Date of Patent: March 8, 2022Assignee: Clarify Health Solutions, Inc.Inventors: Erik Talvola, Emmet Sun, Adam F. Rogow, Jeffrey D. Larson, Justin Warner
-
Patent number: 11238469Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and risk adjusted performance ranking of healthcare providers. Embodiments of computer network architecture automatically make risk adjusted performance rankings of healthcare service providers and generate and transmit reports of the rankings. Embodiments may generate such rankings either occasionally on demand, or periodically, or as triggered by events such as an update of available data for such forecasts. Embodiments may include a combination of third-party databases to generate the updated forecasts for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: May 6, 2019Date of Patent: February 1, 2022Assignee: Clarify Health Solutions, Inc.Inventors: Erik Talvola, Emmet Sun, Adam F. Rogow, Jeffrey D. Larson, Justin Warner
-
Patent number: 10990904Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and automated improvement and regularization of forecasting models, providing rapid improvement of the models. Embodiments may generate such rapid improvement of the models either occasionally on demand, or periodically, or as triggered by events such as an update of available data for such forecasts. Embodiments may indicate, after the improvement of the models, that various web applications using the models may be rerun to seek improved results for the web applications. Embodiments may include a combination of third-party databases to drive the forecasting models, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: July 27, 2020Date of Patent: April 27, 2021Assignee: CLARIFY HEALTH SOLUTIONS, INC.Inventors: Jean P. Drouin, Samuel H. Bauknight, Todd Gottula, Yale Wang, Adam F. Rogow, Jeffrey D. Larson, Justin Warner
-
Patent number: 10923233Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and dynamic patient guidance. Embodiments automatically update patient guidance in the patient care plan, based on the effectiveness of the guidance to date, attributes of the patient, other updated information, ongoing experience of the network, and updated predictions of possible patient outcomes and metrics.Type: GrantFiled: November 25, 2019Date of Patent: February 16, 2021Assignee: CLARIFY HEALTH SOLUTIONS, INC.Inventors: Yale Wang, Samuel H. Bauknight, Adam F. Rogow, Jeffrey D. Larson, Jean P. Drouin
-
Patent number: 10910107Abstract: A computer network architecture for a pipeline of models with machine learning and artificial intelligence for healthcare outcomes is presented. A machine learning prediction module and an artificial intelligence learning model are in electronic communication with a web application, which is also in electronic communication with a user device. An expanding updating database supports automatically recalibrating, re-evaluating, and reselecting the evolving and improving algorithms.Type: GrantFiled: April 10, 2020Date of Patent: February 2, 2021Assignee: CLARIFY HEALTH SOLUTIONS, INC.Inventors: Jeffrey D. Larson, Yale Wang, Samuel H. Bauknight
-
Patent number: 10811139Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and dynamic patient guidance. Embodiments automatically update patient guidance in the patient care plan, based on the effectiveness of the guidance to date, attributes of the patient, other updated information, ongoing experience of the network, and updated predictions of possible patient outcomes and metrics.Type: GrantFiled: June 13, 2018Date of Patent: October 20, 2020Assignee: Clarify Health Solutions, Inc.Inventors: Yale Wang, Samuel H. Bauknight, Adam F. Rogow, Jeffrey D. Larson, Jean P. Drouin
-
Patent number: 10726359Abstract: Embodiments in the present disclosure relate generally to computer network architectures for machine learning, artificial intelligence, and automated improvement and regularization of forecasting models, providing rapid improvement of the models. Embodiments may generate such rapid improvement of the models either occasionally on demand, or periodically, or as triggered by events such as an update of available data for such forecasts. Embodiments may indicate, after the improvement of the models, that various web applications using the models may be rerun to seek improved results for the web applications. Embodiments may include a combination of third-party databases to drive the forecasting models, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.Type: GrantFiled: August 6, 2019Date of Patent: July 28, 2020Assignee: Clarify Health Solutions, Inc.Inventors: Jean P. Drouin, Samuel H. Bauknight, Todd Gottula, Yale Wang, Adam F. Rogow, Jeffrey D. Larson, Justin Warner
-
Patent number: 10650928Abstract: A computer network architecture for a pipeline of models with machine learning and artificial intelligence for healthcare outcomes is presented. A machine learning prediction module and an artificial intelligence learning model are in electronic communication with a web application, which is also in electronic communication with a user device. An expanding updating database supports automatically recalibrating, re-evaluating, and reselecting the evolving and improving algorithms.Type: GrantFiled: December 18, 2017Date of Patent: May 12, 2020Assignee: Clarify Health Solutions, Inc.Inventors: Jeffrey D. Larson, Yale Wang, Samuel H. Bauknight
-
Patent number: 6901451Abstract: One embodiment of the present invention provides a method for communicating transaction request information from a PCI environment over a network. Another embodiment of the present invention provides a method for communicating request packet information from a network to a PCI environment. Another embodiment of the present invention provides a system for communicating transaction request information from a PCI environment over a network. Another embodiment of the present invention provides a system for communicating request packet information from a network to a PCI environment.Type: GrantFiled: October 31, 2000Date of Patent: May 31, 2005Assignee: Fujitsu LimitedInventors: Takashi Miyoshi, Jeffrey D. Larson, Hirohide Sugahara, Takeshi Horie
-
Patent number: 6877039Abstract: A system and method are provided for efficiently writing data from one bus device to another bus device across a network. Data packets to be transmitted are ordered and assigned sequence numbers and expected sequence numbers. The expected sequence number of a data packet corresponds to the sequence number of the data packet immediately prior to the current data packet. When a data packet arrives at the receiving bus, its expected sequence number is compared against the sequence numbers of the previous data packets received. If the previously-received data packet bears the sequence number corresponding to the expected sequence number of the newly arrived data packet, the newly arrived data is stored, and an acknowledgement is sent. If a match cannot be found then a retry request message is sent.Type: GrantFiled: April 25, 2001Date of Patent: April 5, 2005Assignee: Fujitsu LimitedInventors: Jeffrey D. Larson, Takashi Miyoshi, Takeshi Horie, Hirohide Sugahara
-
Patent number: 6804673Abstract: A method and system provide access assurance regarding an RDMA transaction. The system comprises an initiating device and a target device placed across a network. The initiating device and the target device are coupled to a first and a second buses, respectively. The first and the second buses are coupled to the network router through a first and a second network adaptors. An RDMA space and an associated access assurance space are assigned to the target device in the memory space of the first bus. The initiating device may RDMA the target device by directly reading from or writing into the RDMA space assigned to the target device. To obtain access assurance information regarding the RDMA transaction, the initiator performs a read from the assurance space associated with the RDMA space of the target device in the memory space of the first bus.Type: GrantFiled: April 19, 2001Date of Patent: October 12, 2004Assignee: Fujitsu LimitedInventors: Hirohide Sugahara, Jeffrey D. Larson, Takashi Miyoshi, Takeshi Horie
-
Patent number: 6799219Abstract: A method and apparatus for avoiding starvation at an initiator node in a computer network to which are connected at least one target node which provides service and a plurality of initiator nodes which request service from the target node. The method includes: when a request is received from the initiator node during a period that the target node is unable to provide service, returning a reject reply by attaching thereto reject time information that matches the period; when the target node is in a state capable of providing service, preferentially accepting a retry request carrying older reject time information; and when the target node is in the state capable of providing service, returning a reject reply by attaching thereto new reject time information in response to any first request received before retry requests arising from previously rejected requests are all accepted.Type: GrantFiled: August 31, 2000Date of Patent: September 28, 2004Assignee: Fujitsu LimitedInventors: Hirohide Sugahara, Takashi Miyoshi, Takeshi Horie, Jeffrey D. Larson