DiaBD: A Diabetes Dataset for Enhanced Risk Analysis and Research in Bangladesh

This dataset contains 5,288 patient records, covering 14 independent attributes related to demographics, clinical parameters, and medical history. Key features include age, gender, pulse rate, blood pressure (systolic and diastolic), glucose level, BMI, and family history of diabetes, hypertension, and cardiovascular disease. Each patient entry is labeled with a binary diabetes status (diabetic or non-diabetic), making it suitable for predictive modeling and risk assessment.
Designed to facilitate machine learning applications, this dataset supports the development of diabetes detection models, risk stratification, and personalized management strategies. The comprehensive feature set enables researchers to explore patterns in diabetes prevalence and related health factors, thereby contributing to improved early diagnosis and targeted interventions.

本数据集包含5288条患者记录，涵盖与人口统计学、临床参数及病史相关的14项独立属性。核心特征包括年龄、性别、脉搏率、血压（收缩压与舒张压）、血糖水平、身体质量指数（BMI），以及糖尿病、高血压及心血管疾病家族史。每条患者记录均标注有二分类糖尿病状态（糖尿病患者或非糖尿病患者），适用于预测建模与风险评估任务。
本数据集旨在助力机器学习应用开发，可用于构建糖尿病检测模型、开展风险分层研究及制定个性化管理方案。其全面的特征集可支持研究人员探索糖尿病患病率与相关健康因素的分布规律，进而助力优化早期诊断与靶向干预措施。