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发展心血管疾病风险的决定因素,重点是2型糖尿病和利用机器学习算法进行预测建模
Shatabdi Das1, Riaz Rahman1, Ashis Talukder1,2
1Science Engineering and Technology School, Khulna University, Khulna, Bangladesh.
Medicine
|December 10, 2024
概括
2型糖尿病显著增加心血管疾病 (CVD) 的风险,年龄较大和社会经济地位较高是关键决定因素. 机器学习模型准确地预测心血管疾病风险,帮助孟加拉国早期检测和有针对性的干预.
科学领域:
- 心脏病学和公共卫生
- 利用机器学习进行疾病预测.
- 非传染性疾病的流行病学
背景情况:
- 2型糖尿病是一个日益严重的全球健康问题.
- 心血管疾病 (CVD) 是全球死亡的主要原因之一.
- 了解糖尿病特异性心血管疾病风险因素对于预防至关重要.
研究的目的:
- 研究2型糖尿病对心血管疾病 (CVD) 风险的影响.
- 确定孟加拉国高血压患者心血管疾病风险的关键决定因素.
- 开发和评估用于精确预测心血管疾病风险的机器学习 (ML) 模型.
主要方法:
- 来自孟加拉国人口和健康调查 (2011,2017-2018) 数据的分析.
- 应用和比较八个机器学习算法 (SVM,物流回归,决策树,随机森林,天真贝叶斯,KNN,LightGBM,XGBoost).
- 使用六个指标对模型性能进行评估,包括精度和AUC.
主要成果:
- 年龄较大的年龄组 (35-54,55-69,≥70岁) 的心血管疾病风险显著增加.
- 具有较高社会经济地位 ("富人") 和正常到肥胖体重的个人患心血管疾病的风险增加.
- 预测模型表现出高性能,75.21%的准确性和80.79%的AUC;随机森林显示了76.96%的特异性.
结论:
- 年龄,社会经济地位和体重是2型糖尿病患者心血管疾病风险的重要决定因素.
- 机器学习模型为早期心血管疾病风险评估和有针对性的干预提供了一个有希望的方法.
- 研究结果支持需要制定公共卫生战略,以应对生活方式的变化和改善医疗保健准入.
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