RISE:一个新的统一框架,用于营养不良分析的特征相关性,整合统计和专家见解
S Shruthi1, Priya Govindarajan1, S R Shalini2
1Department of Computer Science, School of Computing, Amrita Vishwa Vidyapeetham, Mysuru, India.
Frontiers in public health
|November 3, 2025
概括
确定儿童营养不良的关键因素对于全球卫生目标至关重要. 在RISE框架中,优先考虑母亲身高和母乳养状况等决定因素,改进有针对性的干预措施.
科学领域:
- 公共卫生 公共卫生
- 营养科学 营养科学
- 数据科学数据科学数据科学
背景情况:
- 儿童营养不良是一个关键的全球卫生问题,影响可持续发展目标 (SDGs) 2和3.
- 现有的模型往往低估了儿童急性营养不良的特定环境决定因素.
- 需要一种新的方法来整合数据驱动的见解与领域专业知识,以进行有效的干预.
研究的目的:
- 开发和应用基于相关性的统计和专业知识整合 (RISE) 框架.
- 确定和优先考虑影响急性营养不良的决定因素,在0-23个月的儿童.
- 为了弥合数据建模和特定背景的公共卫生洞察力之间的差距.
主要方法:
- 开发了RISE框架,集成XGBoost模型得分,统计过器和领域专业知识.
- 将RISE应用到迈苏鲁营养康复中心的现实数据中.
- 根据经验实力和领域重要性调整的特征评分.
主要成果:
- RISE框架提高了营养不良预测指标的解释性和上下文相关性.
- 与领域相关的特征,如母亲身高,母乳养状态,种姓,母亲工作状态和粮食配给卡被确定为关键.
- 一贯有影响力的决定因素包括儿童体重,母体人类学和儿童顺序.
结论:
- RISE框架揭示了常常被传统模型遗漏的营养不良的重要贡献者.
- RISE提供了一个可扩展的,情境敏感的方法,以在营养不良研究中确定优先级.
- 这项研究支持为全球营养目标提供更明智,更有针对性的干预措施和政策行动.
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