Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction

Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction

BackgroundEarly identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood transcriptomic analysis provides a minimally invasive approach for identifying predictive biomarkers prior to...

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Bibliographic Details
Main Authors: Xin Huang, Di Ouyang, Weiming Xie, Huawei Zhuang, Siyu Gao, Pan Liu, Lizhong Guo
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Medicine
Subjects:
childhood diabetes
peripheral blood
transcriptomic analysis
machine learning
pediatric biomarkers
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1636214/full
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https://www.frontiersin.org/articles/10.3389/fmed.2025.1636214/full

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