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September 18, 2026BMC Medical Informatics and Decision MakingOpen Access

Machine learning models analyzing screening data from 25,275 individuals successfully identified population-level metabolic breakpoints and individualized risk profiles for diabetes progression.

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Key result

Machine learning models analyzing screening data from 25,275 individuals successfully identified population-level metabolic breakpoints and individualized risk profiles for diabetes progression.

Authors

WGWonmi GuHYHyeonseop YukJMJung Kee Min

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Overview

Study Design

Type

Observational (n=25,275)

PICO

P
Population
25,275 individuals from South Korea with repeated national health screening records between 2014 and 2020, stratified by baseline diabetes status and screening interval.
E
Exposure / Comparator
Screening interval (1-year vs. 2-year) vs 1-year vs. 2-year screening interval
O
Primary Outcome
Diabetes disease progression

Cite This Study

Gu et al. (2026) conducted an observational in Diabetes (n=25,275). Screening interval (1-year vs. 2-year) vs. 1-year vs. 2-year screening interval was evaluated on Diabetes disease progression. Machine learning models analyzing screening data from 25,275 individuals successfully identified population-level metabolic breakpoints and individualized risk profiles for diabetes progression.

synapsesocial.com/papers/6aad0b5cde0393d728b89926https://doi.org/10.1186/s12911-026-03847-w
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