一个大型的语言模型分析全球不平等的精准医学研究糖尿病的研究
Aamna Soniwala1, Sophia Kim2, Jill Welkley1
1Center for the Study of Human Health, College of Arts and Sciences, Emory University, Atlanta, GA, USA.
Annals of epidemiology
|July 6, 2025
概括
针对糖尿病的精准医学研究不成比例地集中在高收入地区. 未来的投资应优先考虑低收入和中等收入国家,以确保在糖尿病护理方面实现全球健康公平.
科学领域:
- 糖尿病研究研究 糖尿病研究
- 精准医学是一门精准的医学.
- 全球卫生公平性全球卫生公平性
背景情况:
- 近80%的糖尿病患者居住在低收入和中等收入国家.
- 目前针对糖尿病的精准医学研究在这些高负担人群中没有很好的特征.
- 手动的文献选是耗时和资源密集的.
研究的目的:
- 描述糖尿病负担和精准医学研究在十个地理区域的比例.
- 使用可扩展的大型语言模型 (LLM) 启用工作流来进行高效的分析.
主要方法:
- 在PubMed的电子搜索中,发现了129,154项关于糖尿病精准医学 (2010-2023) 的研究.
- 一个子样本 (n=2196) 被手动审查,以训练GPT-4o来分类剩余的研究.
- 研究成果被估计为研究与2021年全球疾病负担研究 (GBD) 的残疾调整寿命年 (DALYs) 的比率.
主要成果:
- 在15507项已识别的研究中,33.8%来自北美,20.9%来自西欧,14.3%来自东亚.
- 研究与疾病负担的比例在北美 (0.95/1000 DALYs) 和西欧 (0.78/1000 DALYs) 最高.
- 东南亚,南亚和撒哈拉以南非洲的比例最低 (每一个为0.02/1000 DALY).
结论:
- 目前针对糖尿病的精准医学研究投资与全球疾病负担不一致.
- 研究发现,来自低收入和中等收入国家的研究显著不足.
- 未来的基于OMIC的研究投资应优先考虑北美和西欧以外的地区,以实现糖尿病护理的全球公平.
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