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Diabetes Mellitus: Overview and Type I Subtype

Diabetes Mellitus: Overview and Type I Subtype

Diabetes mellitus is a chronic metabolic disorder characterized by high blood glucose levels due to inadequate insulin production, insulin resistance, or both. The condition affects millions worldwide and can significantly impact their health and quality of life.
Type 1 diabetes is an autoimmune disease in which the immune system mistakenly attacks and destroys the insulin-producing beta cells in the pancreas. As a result, the body is unable to produce sufficient insulin, and individuals with...

Diabetes Mellitus: Type 2 and Gestational

Diabetes Mellitus: Type 2 and Gestational

Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...

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Updated: Aug 14, 2025

Author Spotlight: Network Pharmacology and Molecular Docking to Decipher the Action of Jiawei Shengjiang San Against Diabetic Kidney Disease

Author Spotlight: Network Pharmacology and Molecular Docking to Decipher the Action of Jiawei Shengjiang San Against Diabetic Kidney Disease

Published on: May 10, 2024

Chinese diabetes datasets for data-driven machine learning.

Qinpei Zhao^1,2, Jinhao Zhu¹, Xuan Shen³

¹School of Software Engineering, Tongji University, Shanghai, China.

Scientific Data

|January 18, 2023

Summary

This summary is machine-generated.

Two new datasets, ShanghaiT1DM and ShanghaiT2DM, offer valuable data for diabetes management research. These datasets include patient clinical data, glucose monitoring, and dietary information to advance data-driven diabetes care.

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Area of Science:

Endocrinology and Metabolism
Medical Informatics
Data Science in Healthcare

Background:

Effective diabetes management relies on comprehensive patient data, particularly for data-driven machine learning approaches.
Publicly accessible datasets are crucial for advancing research in diabetes mellitus (DM).

Purpose of the Study:

To introduce and describe the Shanghai Type 1 Diabetes Mellitus (T1DM) and Shanghai Type 2 Diabetes Mellitus (T2DM) datasets.
To make these datasets publicly available to facilitate research in diabetes management.

Main Methods:

Data collected under real-life conditions from Type 1 (n=12) and Type 2 (n=100) diabetic patients in Shanghai, China.
Datasets include clinical characteristics, laboratory measurements, and medication information.
Continuous glucose monitoring (CGM) data (3-14 days) and daily dietary information are provided.

Main Results:

The ShanghaiT1DM and ShanghaiT2DM datasets are now publicly available for research.
The datasets offer rich, real-world data for diabetes management studies.
Comprehensive data includes clinical, biochemical, medication, glucose monitoring, and dietary information.

Conclusions:

The ShanghaiT1DM and ShanghaiT2DM datasets represent a significant contribution to diabetes research resources.
These datasets will support the development of novel data-driven algorithms and technologies for diabetes monitoring and management.
Facilitating research through public data release is key to improving diabetes care outcomes.