US 2021/0343402 A1 · HYPOGLYCEMIC EVENT PREDICTION USING MACHINE LEARNING

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.

Claims25

Dependent claims

A method comprising:

generating instances of training data by selecting time series glucose measurements of a user population for a predefined period of time, identifying, for each time series, a first portion corresponding to a day time interval and a second portion corresponding to a night time interval;
generating, for each instance of training data, a classification label, the classification label defining the instance of training data as hypoglycemic positive or hypoglycemic negative based on the time series glucose measurements of the night time interval;
and
training a machine learning model to predict a hypoglycemic event during the night time interval using the generated instances of training data and the classification labels.

1 more element

One or more computer-readable storage media having instructions stored thereon that are executable by one or more processors to perform operations comprising:

generating instances of training data by selecting time series glucose measurements of a user population for a predefined period of time, identifying, for each time series, a first portion corresponding to a day time interval and a second portion corresponding to a night time interval;
generating, for each instance of training data, a classification label, the classification label defining the instance of training data as hypoglycemic positive or hypoglycemic negative based on the time series glucose measurements of the night time interval;
and
training a machine learning model to predict a hypoglycemic event during the night time interval using the generated instances of training data and the classification labels.

1 more element

Dependencies are inferred from the claim text.

Hypoglycemic event prediction using machine learning

Life of this patent

Hypoglycemic event prediction using machine learning

Life of this patent

Abstract

Claims25