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公开(公告)号：US20210338116A1
公开(公告)日：2021-11-04
申请号：US17114234
申请日：2020-12-07
Applicant: DexCom, Inc.
Inventor： Giada Acciaroli , Mark Derdzinski , Lauren Hruby Jepson , Andrew S. Parker
Abstract: Hypoglycemic event prediction using machine learning is described. A CGM platform includes a machine learning model trained using historical time series glucose measurements of a user population. Once trained, the machine learning model predicts hypoglycemic events for users. When predicting hypoglycemic events, a time series of glucose measurements for a day time interval is received. The glucose measurements of this time series for the day time interval are provided by a CGM system worn by the user. The machine learning model predicts whether a hypoglycemic event will occur during a night time interval that is subsequent to the day time interval by processing the time series of glucose measurements using the trained machine learning model. The hypoglycemic event prediction is then output, such as via communication and/or display of a notification about the hypoglycemic event prediction.
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公开(公告)号：US12205718B2
公开(公告)日：2025-01-21
申请号：US17112870
申请日：2020-12-04
Applicant: DexCom, Inc.
Inventor： Mark Derdzinski , Andrew Scott Parker
IPC: G16H40/67 , A61B5/00 , A61B5/145 , G06F17/18 , G06N3/044 , G06N3/08 , G16H40/63 , G16H50/20 , G06N3/02 , G06N3/0442 , H04L67/12
Abstract: Glucose prediction using machine learning (ML) and time series glucose measurements is described. Given the number of people that wear glucose monitoring devices and because some wearable glucose monitoring devices can produce measurements continuously, a platform providing such devices may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process and covers a robust number of state spaces unlikely to be covered without the enormous amount of data. In implementations, a glucose monitoring platform includes an ML model trained using historical time series glucose measurements of a user population. The ML model predicts upcoming glucose measurements for a particular user by receiving a time series of glucose measurements up to a time and determining the upcoming glucose measurements of the particular user for an interval subsequent to the time based on patterns learned from the historical time series glucose measurements.
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公开(公告)号：US20220361779A1
公开(公告)日：2022-11-17
申请号：US17746475
申请日：2022-05-17
Applicant: Dexcom, Inc.
Inventor： Andrew Parker , Mark Derdzinski , Lauren Jepson , Nathaniel Heintzman , Jacob Leach
Abstract: In implementations of systems for determining a similarity of sequences of glucose values, a computing device implements a similarity system to receive input data describing a sequence of user glucose values measured by a continuous glucose monitoring (CGM) system. The similarity system computes similarity scores for a plurality of sequences of glucose values by comparing each glucose values included in the sequence of user glucose values with ever glucose value included in each sequence of the plurality of sequences. A particular sequence of glucose values that is associated with a highest similarity score is identified. The similarity system determines an externality associated with the particular sequence. The similarity system generates an indication of the externality for display in a user interface.
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公开(公告)号：US20220202320A1
公开(公告)日：2022-06-30
申请号：US17563943
申请日：2021-12-28
Applicant: DexCom, Inc.
Inventor： Alexander Michael Diener , Stacey Fischer , Shaw Strothers , Justin Yuen , Chad Patterson , Apurv Kamath , Drew Terry , Margaret A. Crawford , Mark Derdzinski , Sarah Kate Pickus , Lauren Hruby Jepson , Adam Noar , Douglas Scott Kanter , Sonya Ann Sokolash
Abstract: User interfaces for glucose insight presentation are leveraged. A glucose monitoring application is configured to process glucose measurements to determine one or more glucose insights, e.g., about a user's glucose. The glucose measurements, for example, may be obtained from a glucose monitoring device that collects glucose measurements of the user at predetermined intervals, e.g., every five minutes. The glucose monitoring application configures a user interface, based on configuration data, to present one or more visual elements representative of the one or more glucose insights. For example, the glucose monitoring application may configure the user interface to include a visual element in the form of a color field which represents whether the user's current glucose measurement (e.g., the most recent glucose measurement obtained from the glucose monitoring device) is below, within, or above a glucose range.
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公开(公告)号：US20210375448A1
公开(公告)日：2021-12-02
申请号：US17112828
申请日：2020-12-04
Applicant: DexCom, Inc.
Inventor： Mark Derdzinski , Andrew Scott Parker
Abstract: Glucose prediction using machine learning (ML) and time series glucose measurements is described. Given the number of people that wear glucose monitoring devices and because some wearable glucose monitoring devices can produce measurements continuously, a platform providing such devices may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process and covers a robust number of state spaces unlikely to be covered without the enormous amount of data. In implementations, a glucose monitoring platform includes an ML model trained using historical time series glucose measurements of a user population. The ML model predicts upcoming glucose measurements for a particular user by receiving a time series of glucose measurements up to a time and determining the upcoming glucose measurements of the particular user for an interval subsequent to the time based on patterns learned from the historical time series glucose measurements.
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Patent Agency Ranking
公开(公告)号：US20230138673A1
公开(公告)日：2023-05-04
申请号：US17974299
申请日：2022-10-26
Applicant: DexCom, Inc.
Inventor： Margaret A. Crawford , Mark Derdzinski , Giada Acciaroli , Robert J. Dowd , Lauren H. Jepson , Sarah Kate Pickus , Apurv U. Kamath
Abstract: Feedback regarding diabetes management by a user is generated, such as feedback identifying improvements in glucose measurements for a given time period over previous days, feedback identifying sustained positive patterns, feedback identifying deviations in glucose measurements between time periods, feedback identifying potential behavior modification that a user could take to engage in beneficial diabetes management behavior, feedback identifying what a user's glucose would have been had the particular events or conditions not occurred or not been present, and so forth. A feedback presentation system analyzes the identified feedback and selects feedback based on various rankings, rules and conditions for display to the user. The selected feedback is provided to the user at various times, such as regular reports (e.g., daily or weekly reports), in real time (e.g., notifying the user what his glucose level would have been had he not just taken a walk), and so forth.
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公开(公告)号：US20230135175A1
公开(公告)日：2023-05-04
申请号：US17974185
申请日：2022-10-26
Applicant: Dexcom, Inc.
Inventor： Lauren H. Jepson , Margaret A. Crawford , Mark Derdzinski , Robert J. Dowd , Giada Acciaroli , Sarah Kate Pickus , Apurv U. Kamath
Abstract: Glucose level measurements or other data regarding a user are obtained over time, such as from a wearable glucose monitoring device being worn by the user. These glucose level measurements or other data are analyzed based on various rules to determine time periods during a day of, for example, good diabetes management by the user and provide feedback indicating such to the user. Good diabetes management is identified in various manners, such as by identifying improvements in glucose measurements for a given time period over one or more previous days, identifying a time period of the day during which glucose measurements were the best, identifying sustained positive patterns (e.g., good diabetes management for a same time period in each of multiple days), and so forth.
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公开(公告)号：US20230134919A1
公开(公告)日：2023-05-04
申请号：US17974190
申请日：2022-10-26
Applicant: Dexcom, Inc.
Inventor： Robert J. Dowd , Margaret A. Crawford , Mark Derdzinski , Lauren H. Jepson , Giada Acciaroli , Sarah Kate Pickus , Apurv U. Kamath
Abstract: Glucose level measurements of a user are obtained over time, such as from a wearable glucose monitoring device being worn by the user. These glucose level measurements can be produced substantially continuously, such that the device may be configured to produce the glucose level measurements at regular or irregular intervals of time, responsive to establishing a communicative coupling with a different device, and so forth. These glucose level measurements are analyzed to detect deviations from past glucose measurements, such as glucose measurements received earlier in the day or glucose measurements received at corresponding times of one or more preceding days. Indications of detected deviations are provided to the user or communicated elsewhere, such as to a healthcare professional.
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公开(公告)号：US20210378563A1
公开(公告)日：2021-12-09
申请号：US17334448
申请日：2021-05-28
Applicant: DexCom, Inc.
Inventor： Mark Derdzinski , Joost van der Linden , Robert Dowd , Lauren Hruby Jepson , Giada Acciaroli
Abstract: Glucose measurement and glucose-impacting event prediction using a stack of machine learning models is described. A CGM platform includes stacked machine learning models, such that an output generated by one of the machine learning models can be provided as input to another one of the machine learning models. The multiple machine learning models include at least one model trained to generate a glucose measurement prediction and another model trained to generate an event prediction, for an upcoming time interval. Each of the stacked machine learning models is configured to generate its respective output when provided as input at least one of glucose measurements provided by a CGM system worn by the user or additional data describing user behavior or other aspects that impact a person's glucose in the future. Predictions may then be output, such as via communication and/or display of a notification about the corresponding prediction.
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10.发明授权公开(公告)号：US12289279B2
公开(公告)日：2025-04-29
申请号：US18488898
申请日：2023-10-17
Applicant: Dexcom, Inc.
Inventor： Andrea J. Jackson , Subrai Girish Pai , Mark Derdzinski , Maritza S. Powell , Joost Herman Van Der Linden , Jessica S. Larrabee
IPC: H04L51/214 , G06Q30/0201 , G06Q30/0251
Abstract: Certain aspects of the present disclosure relate to methods and systems for optimized delivery of communications including content to users of a software application. The method also includes obtaining, by a customer engagement platform (CEP), a set of cohort selection criteria for identifying a user cohort to deliver the content; identifying, by a data analytics platform (DAP), the user cohort to communicate with in accordance with the set of cohort selection criteria; identifying, by the DAP, one or more communication configurations for communicating with one or more sub-groups within the user cohort; and to each user of the user cohort, transmitting one or more communications based on the content and a corresponding communication configuration for a sub-group that may include the corresponding user; and measuring engagement outcomes associated with usage of the corresponding one or more communication configurations in communication with each of the sub-groups.
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