公共卫生 公共卫生
Ryan Barnard1, Sarah A Gaussoin1, John P Hepler2
1Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 23, 2025
概括
阿尔茨海默病追踪软件为研究人员提供了实时访问阿尔茨海默病 (AD) 数据,集成先进分析以改善患者风险评估和数据探索. 这种由人工智能驱动的工具增强了AD研究的临床和研究能力.
科学领域:
- 神经科学是一个神经科学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 临床和研究专家面临着从数据库中获取和利用大量健康参数和生物标志物的挑战.
- 现有数据通常代表过时的快照,阻碍及时分析.
- 复杂的机器学习 (ML) 和人工智能 (AI) 分析通常由专家离线执行,限制了可访问性.
研究的目的:
- 开发AD-tracker软件,这是一个模块化和容器化应用程序,用于阿尔茨海默氏症疾病研究中心.
- 解决获取,利用和分析纵向健康数据的挑战.
- 为研究人员提供近乎实时的数据访问和先进的分析能力.
主要方法:
- AD-tracker与机构数据库集成,提供最新的纵向临床,认知和生物标志物数据访问.
- 具有图形化用户界面,有三个模块:风险评估,数据探索器和风险计算器.
- 使用可扩展架构 (Django,PostgreSQL,Redis,Celery) 并支持Linux部署 (Docker,Podman) 进行ML/AI模型集成.
主要成果:
- 一个版本正在韦克森林大学医学院阿尔茨海默氏症疾病中心进行测试.
- 通过在外部网站的成功安装来证明软件的可移植性.
- 初步评估表明,有可能为临床医生和研究人员提供快速数据访问.
结论:
- AD-tracker将数据可视化和复杂的计算相结合,用于近乎实时的数据访问.
- 这是一个人工智能项目,旨在为更广泛的阿尔茨海默病研究社区提供服务.
- 该软件旨在为更广泛的用户提供先进的数据分析功能.
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