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I-Corps: Connected Rapid Innovation Software System to meet Medtech Development Needs

I-Corps: Connected Rapid Innovation Software System to meet Medtech Development Needs
I-Corps:互联快速创新软件系统,满足医疗技术发展需求
批准号:
2154303
负责人:
Fuchiang Tsui
金额:
$5.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-04-01 至 2023-12-31

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中文摘要
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英文摘要
The broader impact/commercial potential of this I-Corps project is the development of artificial intelligence (AI)-driven technology aimed at enhancing interdisciplinary collaboration, mentorship, and talent searching in order to accelerate medical and biotechnological research and product development. A current search for experts commonly depends on word-of-mouth or internet search, which is often time consuming and may not be accurate. The proposed technology may overcome obstacles by 1) facilitating matchmaking to identify collaborators and mentors, and build teams in the context of a voluntary, technical workforce; 2) advancing the understanding of the factors leading to expert or mentor recommendation; and 3) identifying successes/failures in the development of device innovations. The goal of the proposed system is to create impactful, sustained connections within and across institutions, and enable researchers to conduct collaborative research and product deployment that will improve health. This I-Corps project is based on the development of a software system using natural language processing, machine learning, and deep learning to enhance interdisciplinary collaboration, mentorship, and talent identification in order to accelerate medical and biotechnological research and product development. It leverages narrative documents in the public domain and private corporations and performs data fusion across multiple siloed data sources. The proposed innovation may enable users to effectively identify ranked collaborators, mentors, and similar medical products through the AI inference engine based on user's input such as the keywords and abstract. The proposed AI technology leverages distributed free-text databases for search performance and redundancy. Additionally, the this implementation of robust product regulatory pathways may meet the needs of early-stage med-tech developers regardless of their local development ecosystem and connections.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.
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DOI: 10.1016/j.ins.2022.10.032
发表时间: 2022-10
期刊: Inf. Sci.
影响因子: --
作者: [Sifei Han;Lingyun Shi;Russell Richie;F. Tsui]
通讯作者: Sifei Han;Lingyun Shi;Russell Richie;F. Tsui
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