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    SYSTEM-WIDE PROBABILISTIC ALERTING AND ACTIVATION
    1.
    发明申请
    SYSTEM-WIDE PROBABILISTIC ALERTING AND ACTIVATION 审中-公开

    公开(公告)号：US20190034579A1

    公开(公告)日：2019-01-31

    申请号：US16148584

    申请日：2018-10-01

    Applicant: General Electric Company

    Inventor： Andrew Day ,  Christopher Johnson

    IPC: G06F19/00 ,  G16H40/20

    Abstract: Systems, methods, and computer program products that enable system-wide probabilistic forecasting, alerting, optimizing and activating resources in the delivery of care to address both immediate (near real-time) conditions as well as probabilistic forecasted operational states of the system over an interval that is selectable from the current time to minutes, hours and coming days or weeks ahead are provided. There are multiple probabilistic future states that are implemented in these different time intervals and these may be implemented concurrently for an instant in time control, near term, and long term. Those forecasts along with their optimized control of hospital capacity may be independently calculated and optimized, such as for a dynamic workflow direction over the next hour and also a patient's stay over a period of days. In the present application, a probabilistic and conditional workflow reasoning system enabling complex team-based decisions that improve capacity, satisfaction, and safety is provided. A means to consume user(s) judgment, implement control on specific resource assignments and tasks in a clinical workflow is enabled, as is the dynamical and optimal control of the other care delivery assets being managed by the system so as to more probably achieve operating criteria such as throughput, waiting and schedule risk.

    SYSTEM-WIDE PROBABILISTIC ALERTING AND ACTIVATION
    2.
    发明申请
    SYSTEM-WIDE PROBABILISTIC ALERTING AND ACTIVATION 审中-公开
    系统的概念警报和激活

    公开(公告)号：US20160371441A1

    公开(公告)日：2016-12-22

    申请号：US14746385

    申请日：2015-06-22

    Applicant: General Electric Company

    Inventor： Andrew Day ,  Christopher Johnson

    IPC: G06F19/00

    CPC classification number: G06F19/327 ,  G06F19/00 ,  G16H40/20

    Abstract: Systems, methods, and computer program products that enable system-wide probabilistic forecasting, alerting, optimizing and activating resources in the delivery of care to address both immediate (near real-time) conditions as well as probabilistic forecasted operational states of the system over an interval that is selectable from the current time to minutes, hours and coming days or weeks ahead are provided. There are multiple probabilistic future states that are implemented in these different time intervals and these may be implemented concurrently for an instant in time control, near term, and long term. Those forecasts along with their optimized control of hospital capacity may be independently calculated and optimized, such as for a dynamic workflow direction over the next hour and also a patient's stay over a period of days. In the present application, a probabilistic and conditional workflow reasoning system enabling complex team-based decisions that improve capacity, satisfaction, and safety is provided. A means to consume user(s) judgment, implement control on specific resource assignments and tasks in a clinical workflow is enabled, as is the dynamical and optimal control of the other care delivery assets being managed by the system so as to more probably achieve operating criteria such as throughput, waiting and schedule risk.

    Abstract translation: 系统，方法和计算机程序产品，使系统范围内的概率预测，警报，优化和激活资源在提供护理方面处理即时（近实时）条件以及系统的概率预测操作状态 提供从当前时间到分钟，小时和未来几天或几周可选的时间间隔。 在这些不同的时间间隔内实施了多个概率未来状态，这些可能在时间控制，近期和长期的时间上同时实现。 这些预测以及其对医院能力的优化控制可以独立计算和优化，例如在下一个小时的动态工作流方向以及患者在几天内的停留时间。 在本应用中，提供了一个概率和条件工作流推理系统，实现了改进容量，满意度和安全性的基于团队的决策。 消费用户判断，实施对临床工作流程中特定资源分配和任务的控制的手段得以实现，系统管理的其他护理运送资产的动态和最佳控制也可以实现， 诸如吞吐量，等待和进度风险等标准。

    Sensing and computing control system for shaping precise temporal physical states
    3.
    发明授权
    Sensing and computing control system for shaping precise temporal physical states 有权

    公开(公告)号：US10520937B2

    公开(公告)日：2019-12-31

    申请号：US15429515

    申请日：2017-02-10

    Applicant: General Electric Company

    Inventor： Adam Rasheed ,  David Toledano ,  Christopher Johnson

    IPC: G05B23/02

    Abstract: According to some embodiments, system and methods are provided, comprising an installed product, including a plurality of components; a computer programmed with a damage metric model for the installed product, the damage metric model for providing an estimate of an extent of damage on one or more components; the computer programmed with a dynamic process control model for providing a dynamic response of the installed product with respect to its one or more operating parameters; the computer further programmed with a true-up model for providing a control action to reduce an uncertainty of the estimate provided by the damage metric model; the computer including a processor and a memory in communication with the processor, the memory storing the damage metric model and the true-up model; the memory storing additional program instructions, the processor operative with the additional program instructions to perform functions as follows: receiving an estimate output of the damage metric model, wherein the output includes the estimate of the extent of damage on the one or more components; generating, via the dynamic process control model, an operating response of the installed product to the received estimate output; in response to receipt of the estimate output, executing the true-up model; and generating, via execution of the true-up model, the plan to reduce uncertainty of the estimate output. Numerous other aspects are provided.

    OPERATIONS OPTIMIZATION ASSIGNMENT CONTROL SYSTEM WITH COUPLED SUBSYSTEM MODELS AND DIGITAL TWINS
    7.
    发明申请
    OPERATIONS OPTIMIZATION ASSIGNMENT CONTROL SYSTEM WITH COUPLED SUBSYSTEM MODELS AND DIGITAL TWINS 有权

    公开(公告)号：US20210350294A1

    公开(公告)日：2021-11-11

    申请号：US16870212

    申请日：2020-05-08

    Applicant: General Electric Company

    Inventor： Christopher Johnson ,  Lorenzo Escriche ,  Dinakar Deshmukh ,  Michael Arguello ,  Altug Bayram

    IPC: G06Q10/06 ,  G06F30/23

    Abstract: Optimization systems and methods for optimizing business operations and asset systems are disclosed. A system includes digital twins corresponding to asset systems; business models corresponding to business operations; and an electronic control unit (ECU). The ECU is programmed to: implement an asset optimizer module, where implementing the asset optimizer module interconnects the digital twins for optimization; execute the asset optimizer module, where the asset optimizer module optimizes the digital twins to obtain one or more optimization parameters for the asset systems; implement a system optimizer module, where the system optimizer module receives the one or more optimization parameters and the business models; execute the system optimizer module, where the system optimizer module generates operation protocols for the business models; and output, to a user, the operation protocols for implementation in a real-world asset system.

    System-wide probabilistic alerting and activation
    8.
    发明授权
    System-wide probabilistic alerting and activation 有权

    公开(公告)号：US11080367B2

    公开(公告)日：2021-08-03

    申请号：US16148584

    申请日：2018-10-01

    Applicant: General Electric Company

    Inventor： Andrew Day ,  Christopher Johnson

    IPC: G16H40/20 ,  G06F19/00

    Abstract: Systems, methods, and computer program products that enable system-wide probabilistic forecasting, alerting, optimizing and activating resources in the delivery of care to address both immediate (near real-time) conditions as well as probabilistic forecasted operational states of the system over an interval that is selectable from the current time to minutes, hours and coming days or weeks ahead are provided. There are multiple probabilistic future states that are implemented in these different time intervals and these may be implemented concurrently for an instant in time control, near term, and long term. Those forecasts along with their optimized control of hospital capacity may be independently calculated and optimized, such as for a dynamic workflow direction over the next hour and also a patient's stay over a period of days. In the present application, a probabilistic and conditional workflow reasoning system enabling complex team-based decisions that improve capacity, satisfaction, and safety is provided. A means to consume user(s) judgment, implement control on specific resource assignments and tasks in a clinical workflow is enabled, as is the dynamical and optimal control of the other care delivery assets being managed by the system so as to more probably achieve operating criteria such as throughput, waiting and schedule risk.

    System-wide probabilistic alerting and activation
    10.
    发明授权
    System-wide probabilistic alerting and activation 有权

    公开(公告)号：US10089441B2

    公开(公告)日：2018-10-02

    申请号：US14746385

    申请日：2015-06-22

    Applicant: General Electric Company

    Inventor： Andrew Day ,  Christopher Johnson

    IPC: G16H40/20 ,  G06F19/00

    Abstract: Systems, methods, and computer program products that enable system-wide probabilistic forecasting, alerting, optimizing and activating resources in the delivery of care to address both immediate (near real-time) conditions as well as probabilistic forecasted operational states of the system over an interval that is selectable from the current time to minutes, hours and coming days or weeks ahead are provided. There are multiple probabilistic future states that are implemented in these different time intervals and these may be implemented concurrently for an instant in time control, near term, and long term. Those forecasts along with their optimized control of hospital capacity may be independently calculated and optimized, such as for a dynamic workflow direction over the next hour and also a patient's stay over a period of days. In the present application, a probabilistic and conditional workflow reasoning system enabling complex team-based decisions that improve capacity, satisfaction, and safety is provided. A means to consume user(s) judgment, implement control on specific resource assignments and tasks in a clinical workflow is enabled, as is the dynamical and optimal control of the other care delivery assets being managed by the system so as to more probably achieve operating criteria such as throughput, waiting and schedule risk.

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