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Diabetes Mellitus: Overview and Type I Subtype01:22

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A bimodal dataset for diabetes research.

Jiandun Li1, Huiyao Zheng1, Yabin Zhou1

  • 1School of Electronic Information Engineering, Shanghai Dianji University, Shanghai, 201306, China.

Scientific Data
|March 12, 2026
PubMed
Summary

This study introduces a large diabetes dataset with 5,922 examples and 190 attributes. This resource aids research into diabetes progression, complication risks, and related metabolic factors.

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Area of Science:

  • Endocrinology and Metabolism
  • Clinical Data Science

Background:

  • Rising global diabetes prevalence necessitates advanced research tools.
  • Limited availability of large-scale, comprehensive diabetes datasets hinders progress.

Purpose of the Study:

  • To present a novel, large-scale diabetes dataset for research.
  • To facilitate in-depth analysis of diabetes progression and complications.

Main Methods:

  • Dataset compilation of 5,922 patient examples.
  • Inclusion of 190 detailed clinical and demographic attributes.

Main Results:

  • The dataset encompasses BMI, lifestyle, family history, glycemic control, insulin, and metabolic profiles.
  • Provides a foundation for reliable analyses of diabetes-related factors.

Conclusions:

  • This dataset addresses the critical need for comprehensive diabetes data.
  • Enables advanced research into diabetes pathogenesis, risk factors, and management.