来自孟加拉国的2型糖尿病临床数据集,包括人口统计,人体测量和生物化学参数
Md Younus Bhuiyan1, Shahriar Siddique Ayon2, Md Ebrahim Hossain2
1Department of Computer Science, Daffodil International University, 1207 Dhaka, Bangladesh.
Data in brief
|February 2, 2026
概括
这个数据集提供了1065个患者记录,用于孟加拉国2型糖尿病研究. 它有助于开发机器学习模型和了解南亚糖尿病流行病学.
科学领域:
- 生物医学数据科学 生物医学数据科学
- 公共卫生 公共卫生
- 临床信息学 临床信息学
背景情况:
- 2型糖尿病在孟加拉国是一个重大的公共卫生挑战.
- 一个精心策划的患者记录数据集对于推进研究和临床理解至关重要.
研究的目的:
- 为2型糖尿病评估提供1065个患者记录的综合数据集.
- 促进机器学习,流行病学研究和教育应用方面的研究.
主要方法:
- 经过培训的员工在例行临床访问期间收集的数据.
- 包括人口统计,人体统计和临床变量.
- 通过数据检查确保准确性和完整性,并注明腹痛血压和皮肤厚度的缺失值.
主要成果:
- 数据集包括1065个患者记录,其中大多数 (840) 被诊断为2型糖尿病.
- 包括年龄,BMI,血压,禁食葡萄糖,胰岛素和糖尿病血统功能等变量.
- 来自寻求护理的患者的横截面数据,糖尿病患病率较高.
结论:
- 该数据集对于机器学习分类器培训和特征选择基准测试具有价值.
- 支持南亚临床环境中的流行病学描述和模型验证.
- 作为可复制生物医学数据工作流程的教学资源.
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