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DiaBD:一个糖尿病数据集,用于加强孟加拉国的风险分析和研究
Tabia Tanzin Prama1, Md Jobayer Rahman1, Marzia Zaman1,2
1Advanced Intelligent Multidisciplinary Systems (AIMS) Lab, Institute of Research, Innovation, Incubation, and Commercialization (IRIIC), United International University, Dhaka 1212, Bangladesh.
Data in brief
|July 4, 2025
概括
一个新的数据集,DiaBD,提供来自孟加拉国的5288名患者记录,以改善糖尿病研究和医疗保健规划. 该资源有助于进行糖尿病和相关疾病的风险分析和预测建模.
科学领域:
- 公共卫生 公共卫生
- 生物医学信息学 生物医学信息学
- 流行病学 流行病学
背景情况:
- 糖尿病影响全球超过4.63亿成年人,构成重大公共卫生挑战.
- 糖尿病是全球死亡和发病的主要原因.
- 现有研究在不同的人口统计数据中存在差距,特别是在南亚.
研究的目的:
- 介绍DiaBD,一个由5288名孟加拉患者记录组成的新型数据集.
- 解决糖尿病研究,医疗保健规划和风险分析中的关键缺口.
- 促进糖尿病护理中的预测建模和机器学习应用.
主要方法:
- 编制一个具有14个属性的综合数据集 (DiaBD).
- 包括人口统计,临床和人体统计数据.
- 收集有关家族病史,心血管疾病 (CVD) 和中风的信息.
主要成果:
- DiaBD数据集提供了人口多样性和精确的测量.
- 它包括关键指标,如年龄,性别,生命体征,BMI和糖尿病状况.
- 诸如心血管疾病和中风等特征使得研究共患病和相关风险成为可能.
结论:
- DiaBD支持用于糖尿病风险评估的先进机器学习应用程序.
- 该数据集促进了个性化的医疗保健策略和改进的公共卫生规划.
- 研究人员可以使用DiaBD.探索糖尿病,高血压,心血管疾病和中风之间的联系.
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