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    MULTILAYER PERCEPTRON BASED NETWORK TO IDENTIFY BASELINE ILLNESS RISK
    1.
    发明申请
    MULTILAYER PERCEPTRON BASED NETWORK TO IDENTIFY BASELINE ILLNESS RISK 审中-公开

    公开(公告)号：US20200320391A1

    公开(公告)日：2020-10-08

    申请号：US16840856

    申请日：2020-04-06

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Stephanie Lanius ,  Erina Ghosh ,  Emma Holdrich Schwager ,  Larry James Eshelman

    IPC: G06N3/08 ,  G06N3/04 ,  G06N20/00 ,  G06K9/62 ,  G16H50/30 ,  A61B5/20

    Abstract: A method for training a baseline risk model, including: pre-processing input data by normalizing continuous variable inputs and producing one-hot input features for categorical variables; providing definitions for clean input data and dirty input data based upon various input data related to a patient condition; segmenting the input data into clean input data and dirty input data, wherein the clean input data includes a first subset and a second subset, where the first subset and the second subset include all of the clean input data and are disjoint; training a machine learning model using the first subset of the clean data; and evaluating the performance of the trained machine learning model using the second subset of the clean input data and the dirty input data.

    ADAPTING A MACHINE LEARNING MODEL BASED ON A SECOND SET OF TRAINING DATA
    2.
    发明申请
    ADAPTING A MACHINE LEARNING MODEL BASED ON A SECOND SET OF TRAINING DATA 有权

    公开(公告)号：US20210042667A1

    公开(公告)日：2021-02-11

    申请号：US16962599

    申请日：2019-04-16

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Erina Ghosh ,  Larry James Eshelman

    IPC: G06N20/20 ,  G16H50/70 ,  G16H10/60

    Abstract: Systems and methods for adapting a first machine learning model that takes clinical data as input, based on a second set of training data. The first machine learning model having been trained on a first set of training data. The method comprises adding an adaption module to the first machine learning model, the adaption module comprising a second machine learning model, and training the second machine learning model using a second set of training data to take an output of the first machine learning model as input and provide an adjusted output.

    SYSTEM AND METHOD TO COMBINE MULTIPLE PREDICTIVE OUTPUTS TO PREDICT COMPREHENSIVE AKI RISK
    4.
    发明公开
    SYSTEM AND METHOD TO COMBINE MULTIPLE PREDICTIVE OUTPUTS TO PREDICT COMPREHENSIVE AKI RISK 审中-公开

    公开(公告)号：US20230215579A1

    公开(公告)日：2023-07-06

    申请号：US18093843

    申请日：2023-01-06

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Erina Ghosh ,  Emma Holdrich Schwager ,  Larry James Eshelman ,  Kianoush Kashani

    IPC: G16H50/30 ,  G16H10/60

    CPC classification number: G16H50/30 ,  G16H10/60

    Abstract: Systems, apparatuses, and methods provide for the monitoring and/or management of acute kidney injury (AKI). For example, an apparatus (100) is configured to determine whether a baseline AKI risk prediction is above a baseline threshold based on patient demographic data and patient medical history data, and perform a continuous AKI risk prediction. The continuous AKI risk prediction includes determining whether an any risk of AKI prediction is above an any AKI threshold based on dynamic intervention data and/or dynamic patient condition data, and determining an AKI stage prediction in response to a determination that the any risk of AKI prediction is above the any AKI threshold based on the dynamic intervention data and/or the dynamic patient condition data.

    Method to quantify photoplethysmogram (PPG) signal quality
    5.
    发明授权
    Method to quantify photoplethysmogram (PPG) signal quality 有权

    公开(公告)号：US11529101B2

    公开(公告)日：2022-12-20

    申请号：US15777247

    申请日：2016-11-10

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Erina Ghosh ,  Cristhian Mauricio Potes Blandon

    IPC: A61B5/1455 ,  A61B5/00 ,  A61B5/021 ,  A61B5/0245 ,  A61B5/024 ,  G06K9/00 ,  A61B5/35 ,  A61B5/352

    Abstract: When evaluating the quality of photoplethysmography (PPG) signal (52) measured from a patient monitor (e.g., a finger sensor or the like), multiple features of the PPG signal are extracted and analyzed to facilitate assigning a score to the PPG signal or portions (e.g., heartbeats) thereof. Heartbeats in the PPG signal are segmented out using concurrently captured electrocardiograph (ECG) signal (50), and for each heartbeat, a plurality of extracted features are analyzed. If all extracted features satisfy one or more predetermined criteria for each feature, then the heartbeat waveform is compared to a predefined heartbeat template. If the waveform matches the template (e.g., within a predetermined match percentage or the like), then the heartbeat is classified as “clean.” If the heartbeat does not patch the template, or if one or more of the extracted features fails to satisfy its one or more pre-determined criteria, the heartbeat is classified as “noisy.”

    TEMPLATE-BASED ANALYSIS AND CLASSIFICATION OF CARDIOVASCULAR WAVEFORMS
    6.
    发明申请
    TEMPLATE-BASED ANALYSIS AND CLASSIFICATION OF CARDIOVASCULAR WAVEFORMS 有权

    公开(公告)号：US20220313169A1

    公开(公告)日：2022-10-06

    申请号：US17407541

    申请日：2021-08-20

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Erina Ghosh ,  Cristhian Potes ,  Richard Earl Gregg

    IPC: A61B5/00 ,  A61B5/0215 ,  A61B5/0295 ,  A61B5/35 ,  A61B5/316 ,  A61B5/352 ,  A61B5/021

    Abstract: In various embodiments, a first classification assigned to a periodic component of an electrical waveform that represents electrical activity in a patient's heart may be identified. A corresponding periodic component of a hemodynamic waveform that represents hemodynamic activity in the patient's cardiovascular system may be analyzed. The corresponding periodic component may be causally related to the periodic component of the electrical waveform. Based on the analysis, the previously-assigned classification may be assigned to the corresponding periodic component of the hemodynamic waveform in response to a determination, based on the analyzing, that the previously-assigned classification also applies to the corresponding periodic component. In a database of hemodynamic templates, a hemodynamic template associated with the previously-assigned classification may be updated to include one or more features of the corresponding periodic component of the hemodynamic waveform.

    Template-based analysis and classification of cardiovascular waveforms
    7.
    发明授权
    Template-based analysis and classification of cardiovascular waveforms 有权

    公开(公告)号：US11103191B2

    公开(公告)日：2021-08-31

    申请号：US16311453

    申请日：2017-06-12

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Erina Ghosh ,  Cristhian Potes ,  Richard Earl Gregg

    IPC: A61B5/0215 ,  A61B5/0295 ,  A61B5/364 ,  A61B5/366 ,  A61B5/024 ,  A61B5/00 ,  A61B5/35 ,  A61B5/316 ,  A61B5/352 ,  A61B5/021

    Abstract: In various embodiments, a first classification assigned to a periodic component of an electrical waveform that represents electrical activity in a patient's heart may be identified (302). A corresponding periodic component of a hemodynamic waveform that represents hemodynamic activity in the patient's cardiovascular system may be analyzed (306, 318, 328). The corresponding periodic component may be causally related to the periodic component of the electrical waveform. Based on the analysis, the previously-assigned classification may be assigned (312, 324) to the corresponding periodic component of the hemodynamic waveform in response to a determination, based on the analyzing, that the previously-assigned classification also applies to the corresponding periodic component. In a database (130) of hemodynamic templates, a hemodynamic template associated with the previously-assigned classification may be updated (314) to include one or more features of the corresponding periodic component of the hemodynamic waveform.

    AUTO-POPULATING PATIENT REPORTS
    8.
    发明申请
    AUTO-POPULATING PATIENT REPORTS 审中-公开

    公开(公告)号：US20190122750A1

    公开(公告)日：2019-04-25

    申请号：US16094543

    申请日：2017-04-13

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Erina Ghosh ,  Eric Thomas Carlson ,  Oladijemi Feyisetan Farri

    IPC: G16H10/60 ,  G16H10/20 ,  G16H10/40

    Abstract: Various embodiments described herein relate to methods and apparatuses for documenting data by tracking user interactions with an interface. Users such as medical personnel or the like rely on clinical documentation to treat a patient. By automatically generating clinical documentation based on user interactions with an interface when reviewing patient data, users are not required to spend time in generating clinical documentation themselves.

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