Machine Learning-driven Identification of the Honeymoon Phase in Pediatric Type 1 Diabetes and Optimizing Insulin Management

Machine Learning-driven Identification of the Honeymoon Phase in Pediatric Type 1 Diabetes and Optimizing Insulin Management

Objective: The honeymoon phase in type 1 diabetes (T1D) represents a temporary improvement in glycemic control but may complicate insulin management. The aim was to develop and validate a machine learning (ML)-driven method for accurately detecting this phase to optimize insulin therapy and prevent...

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Bibliographic Details
Main Author: Satheeskumar R.
Format: Article
Language:English
Published: Galenos Yayincilik 2025-09-01
Series:JCRPE
Subjects:
honeymoon phase
insulin management
machine learning
type 1 diabetes
Online Access:https://www.jcrpe.org/articles/machine-learning-driven-identification-of-the-honeymoon-phase-in-pediatric-type-1-diabetes-and-optimizing-insulin-management/doi/jcrpe.galenos.2025.2024-8-13
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https://www.jcrpe.org/articles/machine-learning-driven-identification-of-the-honeymoon-phase-in-pediatric-type-1-diabetes-and-optimizing-insulin-management/doi/jcrpe.galenos.2025.2024-8-13

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