使用机器学习技术分析和预测孟加拉国5岁以下死亡率趋势
Shayla Naznin1, Md Jamal Uddin2,3, Ishmam Ahmad4
1Department of Statistics, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
PloS one
|February 7, 2025
概括
孟加拉国5岁以下的死亡率在1994年至2018年期间显著下降了76.72%,下降了76.72%. 机器学习模型准确地预测未来的趋势,尽管如果没有加强干预,可持续发展目标的目标可能无法实现.
科学领域:
- 公共卫生 公共卫生
- 人口统计学 人口统计学
- 数据科学数据科学数据科学
背景情况:
- 5岁以下的死亡率是发展的一个关键指标,特别是在孟加拉国.
- 机器学习模型被用来预测5岁以下的死亡率趋势.
- 为决策者和卫生专业人员提供了可操作的见解.
研究的目的:
- 用机器学习预测孟加拉国5岁以下死亡率的未来趋势.
- 确定最准确的机器学习模型来预测5岁以下的死亡率.
- 为公共卫生干预提供基于数据的建议.
主要方法:
- 分析孟加拉国人口和健康调查 (BDHS) 的数据,从1993-94年到2017-18年.
- 应用各种机器学习算法,包括线性回归,XGBoost和CatBoost.
- 使用MAE,RMSE,R-squared和MAPE等指标进行模型性能评估,并进行k倍交叉验证.
主要成果:
- 从1994年到2018年,孟加拉国在5岁以下的死亡率显著下降.
- 线性回归模型表现出最高准确度,最小的误差指标和最高的R平方.
- 预测显示持续减少,到2030年达到29.87%,到2035年达到每1000名活产婴儿的26.21%.
结论:
- 在孟加拉国,5岁以下的死亡率从1994年到2018年减少了76.72%.
- 线性回归模型准确地预测了5岁以下的死亡趋势.
- 预测的比率可能无法达到可持续发展目标,需要加强医疗保健和孕产妇健康干预.
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