Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Hypoglycemia and Glucagon

Hypoglycemia and Glucagon

Without prolonged fasting, healthy individuals maintain blood glucose levels above 3.5 mM due to a well-adapted neuroendocrine counterregulatory system that effectively prevents acute hypoglycemia, a potentially life-threatening condition. The primary clinical scenarios for hypoglycemia encompass diabetes treatment, inappropriate production of endogenous insulin or insulin-like substances by tumors, and the use of glucose-lowering agents in non-diabetic individuals. Notably, hypoglycemia in the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Mitigating Glycemic Disparities: Understanding Contributions of Sociodemographic Variables in the Teamwork, Targets, Technology, and Tight Glycemia (4T) Study.

The Journal of pediatrics·2026

Same author

Micro-randomization trial design under operational constraints.

Contemporary clinical trials·2026

Same author

Building the evidence to address disparities in type 1 diabetes (BEAD-T1D): methods and design of a study examining barriers and promoters to diabetes device use in families with public insurance.

Frontiers in endocrinology·2026

Same author

Cost-Effectiveness of Continuous Glucose Monitoring With Remote Patient Monitoring in Pediatric Patients With Newly Diagnosed Type 1 Diabetes in the U.S.

Diabetes care·2026

Same author

A Quantitative Framework for Evaluating the Performance of Algorithm-Directed Whole-Population Remote Patient Monitoring: Tutorial for Type 1 Diabetes Care.

JMIR diabetes·2026

Same author

Diabetes Technology and Therapy in the Pediatric Age Group.

Diabetes technology & therapeutics·2026

Search research articles

Related Experiment Video

Updated: Jul 1, 2025

Simple Continuous Glucose Monitoring in Freely Moving Mice

Simple Continuous Glucose Monitoring in Freely Moving Mice

Published on: February 24, 2023

A Machine Learning Model for Week-Ahead Hypoglycemia Prediction From Continuous Glucose Monitoring Data.

Flavia Giammarino¹, Ransalu Senanayake², Priya Prahalad^3,4,5

¹Independent Researcher, Spoltore, PE, Italy.

Journal of Diabetes Science and Technology

|March 6, 2024

Summary

This summary is machine-generated.

This study developed a machine learning model to predict hypoglycemia in type 1 diabetes patients using continuous glucose monitoring data. The model estimates the one-week risk of severe hypoglycemia, aiding remote patient monitoring.

Keywords:

clinical decision support continuous glucose monitoring hypoglycemia prediction machine learning patient prioritization type 1 diabetes

More Related Videos

Improving IV Insulin Administration in a Community Hospital

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli

Published on: August 12, 2016

Related Experiment Videos

Last Updated: Jul 1, 2025

Simple Continuous Glucose Monitoring in Freely Moving Mice

Simple Continuous Glucose Monitoring in Freely Moving Mice

Published on: February 24, 2023

Improving IV Insulin Administration in a Community Hospital

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli

Published on: August 12, 2016

Area of Science:

Artificial Intelligence in Medicine
Diabetes Technology
Predictive Analytics

Background:

Remote patient monitoring (RPM) enhances type 1 diabetes (T1D) care using continuous glucose monitoring (CGM) data.
Limited methods exist to predict clinically significant hypoglycemia within a week.

Purpose of the Study:

Develop a machine learning model to predict the probability of clinically significant hypoglycemia in T1D patients within one week.
Define clinically significant hypoglycemia as CGM readings below 54 mg/dL for at least 15 consecutive minutes.

Main Methods:

Utilized CGM time series data from three T1D cohorts (REPLACE-BG, JDRF, Tidepool).
Developed a machine learning model to predict the one-week risk of hypoglycemia.
Evaluated model performance using 10-fold cross-validation and external validation.

Main Results:

Achieved an average ROC-AUC of 0.77 in 10-fold cross-validation across cohorts.
Demonstrated an average ROC-AUC of 0.74 in external validation.
The model shows promising predictive capabilities for hypoglycemic events.

Conclusions:

A machine learning algorithm was developed to estimate the probability of clinically significant hypoglycemia within one week.
This predictive tool can offer valuable context for RPM providers, aiding in patient prioritization for T1D care.