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September 18, 2025Journal of Clinical MedicineOpen Access

Appraisal of Clinical Explanatory Variables in Subtyping of Type 2 Diabetes Using Machine Learning Models

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Authors

AKAmar Hassan KhamisFAFatima AbdulSDStafny Dsouza

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Overview

Analysis of clinical variables defines distinct type 2 diabetes subtypes, suggesting machine learning can enhance classification.

Key Points

  • Five distinct subtypes of type 2 diabetes were identified, indicating significant clinical diversity.
  • The strongest subgroup concordance was found between severe insulin-resistant diabetes and severe insulin-deficient diabetes.
  • Clustering of type 2 diabetes was validated using multinomial logistic regression for utmost reliability.
  • The integration of probabilistic clustering and machine learning paves the way for improving diabetes care precision.

Cite This Study

Khamis et al. (2025) studied this question.

synapsesocial.com/papers/68d433a3713b0b5dfea72ed1https://doi.org/10.3390/jcm14186548
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  5. 51088-OR: Bridging Omics to Phenotypes: A Deep-Learning Framework for Molecular Characterization of Type 2 Diabetes Subtypes2026