人工智能驱动的模型用于预测孕产妇,新生儿和五岁以下儿童的死亡率:系统审查协议
Yingxiang Huang1, Yuxuan Li2,3, Zheyue Jia2
1Karolinska Institutet, Solna Campus, Stockholm, Sweden.
Systematic reviews
|March 6, 2026
概括
本系统性审查评估了人工智能 (AI) 对孕产妇,新生儿和五岁以下儿童死亡率的预测模型. 它旨在比较模型的准确性和适用性,以改善AI.
科学领域:
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 孕产妇,新生儿和五岁以下儿童的死亡率仍然是关键的全球卫生问题.
- 人工智能 (AI) 通过分析复杂的数据来预测这些死亡率.
- 对人工智能模型的系统评估对于在医疗保健中有效实施至关重要.
研究的目的:
- 系统地评估,综合和比较现有关于人工智能预测模型对孕产妇,新生儿和五岁以下儿童死亡率的文献.
- 评估人工智能模型在降低死亡率方面的准确性,灵敏性和适用性.
- 确保人工智能在产妇和儿童医疗保健中得到高效和有效的应用.
主要方法:
- 遵守系统审查和元分析 (PRISMA) 2020年指南的首选报告项目.
- 在14个数据库 (如PubMed,Embase,Scopus) 中进行全面搜索.
- 整合,评估和比较基于透明度,标准化,公平性,模型性能,概括性和异质性的文章.
- 在可能的情况下,将进行元分析,以确定优秀的模型.
主要成果:
- 本节不适用,因为输出是系统审查的协议,而不是审查本身.
- 预期的挑战包括识别偏见和异质性,建立合成标准和解决统计依赖性.
- 建议的解决方案包括结构化的偏差分类学,分层合成规则和强大的统计方法.
结论:
- 本协议详细介绍了人工智能对母婴死亡率预测模型的系统审查方法.
- 该审查预计将解决有关人工智能模型性能和适用性的当前知识差距.
- 调查结果将为推进人工智能在母婴医疗保健中的应用提供见解.
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