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January 1, 2026International Journal of Biomedical Engineering and Technology

Predicting Adolescent Type 2 Diabetes Using an Intelligent System

Mrko Arsenovic Juliens Baker Livija Cveticanin

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Key Points

The aim is to develop a predictive system for adolescent type 2 diabetes risk.
Implemented an intelligent system for predicting diabetes risk in adolescents.
Analyzed data using advanced algorithms and statistical methods to identify key predictors.
Collected health metrics and relevant lifestyle factors from participants.
The predictive model achieved an accuracy rate of 85%, identifying high-risk adolescents effectively.
Key factors included BMI and family history of diabetes as major contributors.
The model suggests potential of early intervention strategies to prevent diabetes.

Implication

Study predicts type 2 diabetes in adolescents, suggesting new prevention strategies.

Abstract

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Cite This Study

Arsenovic et al. (2026) studied this question.

synapsesocial.com/papers/6a13e7a80e02ee3982d32472 https://doi.org/10.1504/ijbet.2026.10078672

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