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.

这个小企业创新研究（SBIR）第一阶段项目的更广泛/商业影响如下。科学文献的指数增长带来了两个关键挑战：（1）在研究设计期间遗漏重要的先前研究可能导致资源和时间浪费，错误的结论和错过的发现，以及（2）有效地利用原始文本形式的大量科学知识变得越来越困难。该项目旨在构建具有颠覆性和商业价值的产品，以应对这些挑战，使制药行业和学术研究受益。此外，该项目在开发先进人工智能技术方面的成功将对佛罗里达州塔拉哈西以及更广泛的美国东南部地区的人工智能产业的增长和发展产生重大影响。这个小企业创新研究（SBIR）第一阶段项目旨在开发人工智能驱动的，商业上可行的应用，通过最近使用获奖的自然语言处理（NLP）管道构建的大规模生物医学知识图（KG）实现。通过整合因果关系，KG进一步转变为因果KG，并通过纳入40个公共数据库的数据和一些常用基因组数据集的分析结果进行增强。为了方便无缝访问KG，项目团队开发了一个名为iExplore的通用查询界面。该界面可以实现高度准确的信息检索，并支持因果推理，为用户提供有价值的见解。在目前的项目中，Insilicom LLC将进一步扩大KG的覆盖范围，并建立一个名为iPulse的新型文献警报系统。通过结合人工智能的进步，知识图谱的丰富性以及查询界面和文献警报系统的实用性，该项目将产生实际和商业上可行的应用程序，这些应用程序将彻底改变生物医学知识的访问，解释，该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准。