SBIR Phase I: Knowledge Graph-powered Information Retrieval and Causal Inference

SBIR 第一阶段：知识图谱驱动的信息检索和因果推理

• 批准号: 2335357
• 负责人: Jinfeng Zhang
• 金额: $ 27.5万
• 依托单位: INSILICOM LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335357&HistoricalAwards=false
• 关键词: SBIR; Phase; Knowledge; Graph; powered

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is as follows. The exponential growth of scientific literature poses two critical challenges: (1) missing important prior studies during research design can lead to resource and time wastage, incorrect conclusions, and missed discoveries, and (2) effectively utilizing the vast volume of scientific knowledge in raw text form has become increasingly difficult. This project aims to build disruptive, commercially valuable products that address these challenges, benefiting the pharmaceutical industry and academic research. In addition, the success of the project in developing advanced AI technologies will have a significant impact on the growth and development of the AI industry in Tallahassee, FL, and the broader southeast region of the United States.This Small Business Innovation Research (SBIR) Phase I project aims to develop AI-powered, commercially viable applications enabled by a large-scale biomedical knowledge graph (KG) constructed recently using an award-winning natural language processing (NLP) pipeline. The KG has been further transformed into a causal KG by integrating causal relations and enhanced by incorporating data from 40 public databases and analysis results of some commonly used genomics datasets. To facilitate seamless access to the KG, the project team has developed a versatile query interface named iExplore. This interface enables highly accurate information retrieval and supports causal inference, providing users with valuable insights. In the current project, Insilicom LLC will further increase the coverage of the KG and build a novel literature alert system called iPulse. By combining the advancements in AI, the richness of the knowledge graph, and the utility of the query interface and literature alert system, this project will result in practical and commercially viable applications that will revolutionize the way biomedical knowledge is accessed, interpreted, and utilized.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.

这项小型企业创新研究（SBIR）I期项目的更广泛/商业影响如下。科学文献的指数增长提出了两个关键挑战：（1）研究设计期间缺少重要的先前研究可能会导致资源和时间浪费，结论不正确和发现发现，并且（2）有效利用原始文本形式的大量科学知识变得越来越困难。该项目旨在建立破坏性的，商业上有价值的产品，以应对这些挑战，从而使制药行业和学术研究受益。此外，该项目在开发高级AI技术方面的成功将对塔拉哈西，佛罗里达州AI行业的增长和发展产生重大影响（NLP）管道。通过整合因果关系，将KG进一步转化为因果KG，并通过合并了40个公共数据库的数据以及一些常用基因组学数据集的分析结果来增强。为了促进无缝访问KG的访问，该项目团队开发了一个名为IExplore的多功能查询界面。该界面可实现高度准确的信息检索并支持因果推理，从而为用户提供了宝贵的见解。在当前的项目中，Insilicom LLC将进一步增加KG的覆盖范围，并建立一个名为Ipulse的新文献警报系统。通过结合AI中的进步，知识图的丰富性以及查询界面和文献警报系统的实用性，该项目将导致实用且在商业上可行的应用程序，这些应用将彻底改变访问，解释和利用生物医学知识的方式，这反映了NSF的法定任务和审查的范围，这是通过评估的范围来弥补的。