Back to search

Article

Predicting Type 2 Diabetes Metabolic Phenotypes Using Continuous Glucose Monitoring and a Machine Learning Framework

2024-07-22

Abstract excerpt

Type 2 diabetes (T2D) and prediabetes are classically defined by the level of fasting glucose or surrogates such as hemoglobin HbA1c. This classification does not take into account the heterogeneity in the pathophysiology of glucose dysregulation, the identification of which could inform targeted approaches to diabetes treatment and prevention and/or predict clinical outcomes. We performed gold-standard metabolic...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
d940e837-6710-58ee-9972-3cfa0a454346
DOI
10.1101/2024.07.20.24310737
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Predicting Type 2 Diabetes Metabolic Phenotypes Using Continuous Glucose Monitoring and a Machine Learning FrameworkDOI 10.1101/2024.07.20.24310737
Prediction of metabolic subphenotypes of type 2 diabetes via continuous glucose monitoring and machine learning.Semantic proximity
Use of Continuous Glucose Monitoring With Machine Learning to Identify Metabolic Subphenotypes and Inform Precision Lifestyle Changes.Semantic proximity
Unmasking Hidden Dysglycemia: A Mobile OGTT Approach Using Continuous Glucose MonitorsSemantic proximity
Continuous Glucose Monitoring Reveals Glycemic Patterns Associated with End-Organ Alterations in Early DysglycemiaSemantic proximity
Domain-based basal and daytime ambulatory glycemic exposure metrics derived from continuous glucose monitoring: a real-world clinic-based studySemantic proximity
Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.Semantic proximity
Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study.Semantic proximity
A Comparison of Daily Glucose Fluctuation Between GCK-MODY and Type 2 Diabetes Using Continuous Glucose Monitoring Technology. Diabetes 2023;72:812-818.Semantic proximity
Cohort profile: the ‘Biomarkers of heterogeneity in type 1 diabetes’ study – a prospective cohort study of clinical and metabolic phenotyping of individuals with long-standing type 1 diabetesSemantic proximity
Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.Semantic proximity
Heterogeneity of Insulin Resistance Surrogates in Thousands of Non-Diabetic Adults: Multi-Modal Data Reveals Discordant Metabolic PhenotypesSemantic proximity
Enhancing Type 1 Diabetes Immunological Risk Prediction with Continuous Glucose Monitoring and Genetic Profiling.Semantic proximity
Select a neighboring publication to make it the new centre.