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Updated: Jul 27, 2025

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在日本成年人中评估多维医疗保健参数,以开发虚拟人类生成模型:横截面研究协议
Masanobu Hibi1, Shun Katada1, Aya Kawakami2
1Biological Science Research, Kao Corporation, Tokyo, Japan.
JMIR research protocols
|June 9, 2023
概括
这项研究收集了997名成年人的综合健康数据,以创建一个虚拟的人类生成模型. 该模型将揭示个性化医疗保健的各种健康指标之间的关系.
科学领域:
- 多学科健康科学 多学科健康科学
- 生物统计学 生物统计学
- 个性化医疗是个性化的医疗.
背景情况:
- 人类的健康状况是通过使用各种参数来评估的.
- 了解健康参数之间的统计关系可以实现个性化和预防性的医疗保健.
- 确定可修改的风险因素 (生活方式,饮食,体育活动) 对于最佳的治疗设计至关重要.
研究的目的:
- 编制一个高维度,横截面数据集,提供全面的健康信息.
- 为分析多维健康数据构建一个联合概率分布模型.
- 促进进一步研究各种健康变量之间的个人关系.
主要方法:
- 一项涉及997名成年参与者 (年龄≥20岁) 的横截面观察性研究.
- 数据收集包括生化,代谢,细菌,遗传 (mRNA),蛋白质组,代谢组,生活方式,功能和嗅觉的个人资料.
- 统计分析包括训练一个共同的概率分布模型和调查个别变量关系.
主要成果:
- 在2021年10月至2022年2月期间,收集了997名参与者的数据.
- 收集的数据将被用来开发一个虚拟的人类生成模型.
- 预计该模型和数据将阐明不同健康状况之间的关系.
结论:
- 预计健康状况之间的相关性会影响个人健康结果.
- 这项研究将支持基于证据的,针对特定人群的干预措施的开发.
- 这些发现将促进个性化和预防性医疗保健战略的发展.
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