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September 5, 2025Diabetes Obesity and Metabolism

Proteomics‐enabled learning machine algorithms enhance the prediction of cardiovascular diseases in patients with type 2 diabetes mellitus

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Authors

BYBowei YuJLJiang LiYYYuefeng Yu

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Overview

Study reveals machine learning combined with proteomics improves cardiovascular disease prediction in patients with type 2 diabetes mellitus, suggesting a personalized approach.

Key Points

  • The full model significantly improved cardiovascular disease prediction accuracy in patients with type 2 diabetes.
  • The area under the receiver operating characteristic curve (AUC) of the full model was 0.81 for 3 years, outperforming conventional models.
  • Using Cox regression and random survival forest algorithms, the study effectively combined clinical data with proteomic data.
  • The model's applicability may be limited due to sample size and clinical constraints associated with proteomics.

Cite This Study

Yu et al. (2025) studied this question.

synapsesocial.com/papers/68c239a3b210217d6477d045https://doi.org/10.1111/dom.70064
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