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公开(公告)号：US10762984B2
公开(公告)日：2020-09-01
申请号：US13955424
申请日：2013-07-31
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Richard Vdovjak , Anca Ioana Daniela Bucur
Abstract: A method provides fully autonomous patient matching by entities of a federated healthcare system. The method includes receiving an electronically formatted query for a patient from an autonomous healthcare entity in a federation of healthcare entities. The query includes at least an identifier of the entity, a unique patient identifier of the patient generated by the entity, and demographics of the patient. The method further includes searching a federated master patient index stored in master patient index storage for an entry likely to correspond to the patient. The method further includes identifying an entry for the patient. The method further includes updating the identified entry to include at least the identifier of the entity, the unique patient identifier of the patient generated by the entity and the demographics.
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公开(公告)号：US20230351252A1
公开(公告)日：2023-11-02
申请号：US18030175
申请日：2021-09-23
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Ashul Jain , Shreya Anand , Shiva Moorthy Pookala Vittal , Aleksandr Bukharev , Richard Vdovjak , Rithesh Sreenivasan
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: Some embodiments are directed to training a model, e.g., a medical model. The training uses multiple model updates received from multiple client systems. At least some of the multiple client train on training sets that indicate values for different features. The model updates are aggregated in an aggregated model, for which feature weights are obtained. The feature weights provide information on the relative importance of the multiple features for the aggregated model's output.
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公开(公告)号：US20170357946A1
公开(公告)日：2017-12-14
申请号：US14572984
申请日：2014-12-17
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Qin Zhu , Yihui Fan , Zuofeng Li , Richard Vdovjak
CPC classification number: G06Q10/1095 , G06Q50/22
Abstract: Embodiments of the present invention relate to clinical knowledge driven healthcare scheduling. There is disclosed a method of healthcare scheduling, comprising receiving a request to generate an appointment for a target user, the request at least containing identification of the target user; obtaining clinical knowledge associated with the target user by accessing a knowledge base, the clinical knowledge at least indicating time constraints and at least one required resource for the appointment; generating a group of prioritized candidate appointments by processing the request at least partially based on the obtained clinical knowledge, each of the candidate appointments being represented at least by appointment time and a priority; and selecting at least one recommended appointment from the group of prioritized candidate appointments based on availability of the at least one required resource. Corresponding apparatus, system and computer program product are also disclosed.
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公开(公告)号：US09348813B2
公开(公告)日：2016-05-24
申请号：US14368938
申请日：2012-12-17
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Gabriel Ryan Mankovich , Richard Vdovjak , Anca Ioana Daniela Bucur , Yuechen Qian , Merlijn Sevenster , Thusitha Dananjaya De Silva Mabotuwana
CPC classification number: G06F17/2785 , G06F17/241 , G06F17/30731 , G16H10/60 , G16H15/00
Abstract: A text analysis system is described. A natural language input unit (1) is arranged for enabling a user to input a free text (10) in a natural language. A natural language processing unit (2) is arranged for processing at least a portion of the free text (10) while it is being inputted, to obtain an explicit representation (11) of semantics represented by the free text. An explicit information input unit (3) is arranged for enabling the user to input explicit information (12) relating to the explicit representation (11) of semantics. The system comprises a visualization unit (4) for visualizing at least part of the explicit representation (11) to the user while the user is still inputting the free text (10). A user interface (5) is arranged for providing a user with simultaneous access to both the natural language input unit (1) and the explicit information input unit (3).
Abstract translation: 描述文本分析系统。 自然语言输入单元（1）被布置为使得用户能够以自然语言输入自由文本（10）。 自然语言处理单元（2）被布置用于在输入自由文本（10）的至少一部分的同时处理，以获得由自由文本表示的语义的显式表示（11）。 显示信息输入单元（3）被布置为使得用户能够输入与语义的显式表示（11）相关的显式信息（12）。 该系统包括可视化单元（4），用于在用户仍然输入自由文本（10）的同时，向用户可视化至少部分显式表示（11）。 用户接口（5）被布置为向用户提供对自然语言输入单元（1）和显式信息输入单元（3）的同时访问。
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公开(公告)号：US20210065054A1
公开(公告)日：2021-03-04
申请号：US16924326
申请日：2020-07-09
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Hongchao Nie , Richard Vdovjak
IPC: G06N20/00 , G06N7/00 , G06F16/242
Abstract: Techniques are described herein for prioritizing tasks of domain experts for machine learning model training. In various embodiments, prediction candidates, such as physiological abnormalities of interest, may be assigned priorities for use in labeling training examples that are to be used to train machine learning model(s). The plurality of training examples may be analyzed to generate a corresponding plurality of preliminary predictions. Each preliminary prediction may include a probability that the respective training example of the plurality of training examples includes at least one of the plurality of prediction candidates. A computing device operated by a domain expert may provide output that presents at least some of the plurality of training examples to the domain expert in a manner selected based on the priorities assigned to the plurality of prediction candidates and the plurality of preliminary predictions.
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Patent Agency Ranking
公开(公告)号：US20160070883A1
公开(公告)日：2016-03-10
申请号：US14838546
申请日：2015-08-28
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Anca Ioana Daniela Bucur , Richard Vdovjak
IPC: G06F19/00
Abstract: The execution of a clinical trial is supported in the following manner. Patient model data is provided for modeling a patient-level workflow in the clinical trial in accordance with a trial protocol. Clinical data of patients participating in the clinical trial is accessed. Using a workflow engine, an instance of the patient-level workflow is instantiated for each of the patients to obtain a plurality of patient-level workflow instantiations. Each of the patient-level workflow instantiations is executed independently based on the clinical data of each respective one of the patients. The patient model data may comprise or be linked to a rule associated with a step of the patient-level workflow. The rule may be executed when the workflow engine reaches the step in one of the patient-level workflow instantiations. Accordingly, a virtual representation of the clinical trial on a patient-level is obtained which represents the actual state of the clinical trial yet which is computer-accessible. Having such a virtual representation of the clinical trial allows the clinical trial to be easily monitored, actively managed, etc., thereby facilitating its execution.
Abstract translation: 以下列方式支持临床试验的执行。 提供患者模型数据，用于根据试验方案对临床试验中的患者级工作流进行建模。 参与临床试验的患者的临床资料。 使用工作流引擎，为每个患者实例化患者级工作流的实例，以获得多个患者级工作流实例。 基于每个患者的临床数据，独立地执行每个患者级工作流实例。 患者模型数据可以包括或者与与患者级工作流程的步骤相关联的规则链接。 当工作流引擎到达其中一个病人级工作流程实例中的步骤时，可以执行该规则。 因此，获得了代表临床试验的实际状态的病人级别的临床试验的虚拟表示，其中计算机可访问。 具有临床试验的这种虚拟表示允许临床试验易于监测，主动管理等，从而便于其执行。
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公开(公告)号：US20160019350A1
公开(公告)日：2016-01-21
申请号：US14744509
申请日：2015-06-19
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Richard Vdovjak , Anca Ioana Daniela Bucur
IPC: G06F19/00 , H04N21/435 , H04N5/783
CPC classification number: G16H10/60 , G16H15/00 , H04N5/783 , H04N21/435
Abstract: A system is provided for visually rendering longitudinal patient data. The system makes use of a screen template defining at least one visual element for being rendered on a display, with an appearance of the visual element being defined by a visualization parameter. The screen template associates the visual element with a clinical decision rule. During operation, longitudinal patient data is accessed and analyzed, namely by evaluating the clinical decision rule using a time portion of the longitudinal patient data as input to obtain a rule output, and by determining the visualization parameter of the visual element based on the rule output. The visual element is then rendered on the display in accordance with the visualization parameter, namely as part of the screen template. This yields a rendering which enables a user to more efficiently process the large amount of data provided by longitudinal patient data. Preferably, the screen template is animated based on the variation in the rule output over the different time portions of the longitudinal patient data.
Abstract translation: 提供用于视觉呈现纵向患者数据的系统。 系统利用屏幕模板定义至少一个视觉元素以在显示器上呈现，其中可视元素的外观由可视化参数定义。 屏幕模板将视觉元素与临床决策规则相关联。 在手术期间，纵向患者数据被访问和分析，即通过使用纵向患者数据的时间部分作为输入来评估临床决策规则以获得规则输出，并且基于规则输出确定可视元素的可视化参数 。 视觉元素然后根据可视化参数（即作为屏幕模板的一部分）在显示器上呈现。 这产生了渲染，使得用户能够更有效地处理由纵向患者数据提供的大量数据。 优选地，屏幕模板基于纵向患者数据的不同时间部分上的规则输出的变化而被动画化。
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公开(公告)号：US20140343925A1
公开(公告)日：2014-11-20
申请号：US14368938
申请日：2012-12-17
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Gabriel Ryan Mankovich , Richard Vdovjak , Anca Ioana Daniela Bucur , Yuechen Qian , Merlijn Sevenster , Thusitha Dananjaya De Silva Mabotuwana
IPC: G06F17/27
CPC classification number: G06F17/2785 , G06F17/241 , G06F17/30731 , G16H10/60 , G16H15/00
Abstract: A text analysis system is described. A natural language input unit (1) is arranged for enabling a user to input a free text (10) in a natural language. A natural language processing unit (2) is arranged for processing at least a portion of the free text (10) while it is being inputted, to obtain an explicit representation (11) of semantics represented by the free text. An explicit information input unit (3) is arranged for enabling the user to input explicit information (12) relating to the explicit representation (11) of semantics. The system comprises a visualization unit (4) for visualizing at least part of the explicit representation (11) to the user while the user is still inputting the free text (10). A user interface (5) is arranged for providing a user with simultaneous access to both the natural language input unit (1) and the explicit information input unit (3)
Abstract translation: 描述文本分析系统。 自然语言输入单元（1）被布置为使得用户能够以自然语言输入自由文本（10）。 自然语言处理单元（2）被布置用于在输入自由文本（10）的至少一部分的同时处理，以获得由自由文本表示的语义的显式表示（11）。 显示信息输入单元（3）被布置为使得用户能够输入与语义的显式表示（11）相关的显式信息（12）。 该系统包括可视化单元（4），用于在用户仍然输入自由文本（10）的同时，向用户可视化至少部分显式表示（11）。 用户界面（5）被布置为提供用户同时访问自然语言输入单元（1）和显式信息输入单元（3）两者，
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公开(公告)号：US20230394320A1
公开(公告)日：2023-12-07
申请号：US18032838
申请日：2021-10-14
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Shreya Anand , Anshul Jain , Shiva Moorthy Pookala Vittal , Aleksandr Bukharev , Richard Vdovjak
IPC: G06N3/098
CPC classification number: G06N3/098
Abstract: Some embodiments are directed to a federated learning system. A federated model is trained on respective local training datasets of respective multiple edge devices. In an iteration, an edge device obtains a current federated model, determines a model update for the current federated model based on the local training dataset, and sends out the model update. The edge device determines the model update by applying the current federated model to a training input to obtain at least a model output for the training input; if the model output does not match a training output corresponding to the training input, include the training input in a subset of filtered training inputs to be used in the iteration; and determining the model update by training the current federated model on only the subset of filtered training inputs.
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公开(公告)号：US20220076078A1
公开(公告)日：2022-03-10
申请号：US17351311
申请日：2021-06-18
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Richard Vdovjak
Abstract: Some embodiments are directed to training method a classifier. The classifier receives sensor data as input and produces a label as output. A quality estimator is applied to meta-data of a training sample, obtaining a quality estimation of a ground-truth label of the training sample. The classifier may be trained on the training sample taking into account the quality of the ground-truth label.
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