国家卫生研究院正在发展的网络基础设施,以支持生物医学研究中的数据和人工智能
Ojas A Ramwala1, Nick Weber2, Sean D Mooney3
1Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, 98195, USA, ramwala@uw.edu.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|February 27, 2026
概括
生物医学研究产生大量数据,需要安全访问和先进的人工智能 (AI) 工具. 国家卫生研究院 (NIH) 正在开发网络基础设施,为科学家们民主化数据和计算资源.
科学领域:
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
- 数据科学数据科学数据科学
背景情况:
- 生物医学正在经历数据生成的指数级增长,这是技术进步所推动的.
- 有效利用这些数据需要强大的计算技术和人工智能 (AI) 算法.
- 在为研究人员提供对生物医学数据和计算资源的安全访问方面存在挑战.
研究的目的:
- 突出在获取生物医学数据集和计算基础设施方面的挑战.
- 介绍国家卫生研究院 (NIH) 关于数据和人工智能生态系统的倡议.
- 通过改进的网络基础设施,讨论推动生物医学研究的解决方案.
主要方法:
- 审查生物医学数据处理当前的技术进步.
- 分析研究人员在数据安全和资源可访问性方面的挑战.
- 概述NIH的战略举措和网络基础设施组件.
主要成果:
- 确定阻碍研究人员获得关键数据和计算工具的关键障碍.
- 介绍NIH的新型网络基础设施,旨在实现访问的民主化.
- 强调需要标准化的IT解决方案,资金和指导.
结论:
- 推进生物医学研究需要克服数据访问和计算资源挑战.
- 美国国家卫生研究院的网络基础设施旨在为生物计算科学家提供安全的数据和云资源.
- 有效的数据科学和人工智能生态系统对于未来的生物医学发现至关重要.
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