Proto-OKN Theme 1: A Dynamically-Updated Open Knowledge Network for Health: Integrating Biomedical Insights with Social Determinants of Health

该项目旨在通过纳入健康的社会决定因素(SDoH)数据来扩大当前的生物医学知识图谱，尽管这些数据已被证明与健康结果有关，但这些数据通常没有得到充分利用。目标是创建一个全面的健康知识图谱，将生物医学事实和来自科学文献和电子健康记录的SDoH数据结合起来。至关重要的是，这一模式将允许持续更新正在进行的生物医学和临床文本数据流，促进新研究成果的快速传播，并促进不断发展的生物医学和公共卫生领域的合作。组织、分析和应用生物医学信息的生物医学知识图谱(KGs)很少包含与非临床因素相关的数据，如社会经济地位、教育和就业，这些数据已被证明与几种健康结果相关。至关重要的是，将SDoH整合到开放的知识库中，以加强改善健康的努力，并减少医疗保健资源可获得性方面的持续差距。这种整合的一个结果将是一个全面的健康知识网络，它将生物医学事实与SDoH数据结合在一起。这个网络可以不断地用新数据更新自己。这一努力面临的挑战包括数据集成、数据流的动态性质，以及以公平和道德的方式将生物医学知识与SDoH数据相结合的需要。为了应对这些挑战，该项目将建立一个多维知识网络，能够支持各种应用程序的复杂查询，并自动核实信息质量。该项目还将把幼儿园与电子健康记录联系起来，揭示社会决定因素与健康结果之间的联系，从而改善医疗结果，促进健康公平。该项目通过提高语义互操作性、改进知识表示、实现自适应知识获取、确保知识图谱的可信性和提高伦理意识来进行创新。它的目标是产生一个全面的知识网络、开源算法、模型和工具，将SDoH事实和数据整合在一起。该项目创建的工具的可获得性将加速知识发现，提高对人类健康和弱势群体福祉的了解。此外，该项目将通过特别研讨会课程和持续的多样性倡议，对学生的教育做出重大贡献。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to expand current biomedical knowledge graphs by incorporating Social Determinants of Health (SDoH) data, which are typically underutilized despite their proven connection to health outcomes. The goal is to create a comprehensive health knowledge graph that combines biomedical facts and SDoH data from scientific literature and Electronic Health Records. Crucially, this model will allow for continuous updates from ongoing streams of biomedical and clinical text data, promoting swift distribution of new research findings and fostering collaboration in the ever-evolving biomedical and public health fields. Biomedical knowledge graphs (KGs), which organize, analyze, and apply biomedical information, rarely incorporate data related to non-clinical factors like socioeconomic status, education, and employment, that have proven correlations with several health outcomes. It is crucial to integrate SDoH into open knowledge repositories to enhance health improvement efforts and to reduce persistent disparities in healthcare resource accessibility. One outcome of this integration would be a comprehensive knowledge network for health that merges biomedical facts with SDoH data. This network could continually update itself with new data. Challenges to this endeavor include data integration, the dynamic nature of data streams, and the need to combine biomedical knowledge with SDoH data in an equitable and ethical manner. To address these challenges, the project will create a multi-dimensional knowledge network capable of supporting complex queries across various applications and automatically verifying information quality. The project will also link the KGs with electronic health records to uncover associations between social determinants and health outcomes, thereby improving healthcare outcomes and promoting health equity. This project innovates by advancing semantic interoperability, improving knowledge representation, enabling adaptive knowledge acquisition, ensuring knowledge graph trustworthiness, and promoting ethical awareness. It aims to yield a comprehensive knowledge network, open-source algorithms, models, and tools that integrate SDoH facts and data. The accessibility of the tools created in this project will accelerate knowledge discovery, improving the understanding of human health and the wellbeing of vulnerable populations. Additionally, this project will significantly contribute to the education of students, particularly those from underrepresented groups, through special seminar courses and ongoing diversity initiatives.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.