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IRES Track I: International Research Experience for Students on Artificial Intelligence for Congenital Heart Diseases

IRES Track I: International Research Experience for Students on Artificial Intelligence for Congenital Heart Diseases
IRES Track I:先天性心脏病人工智能学生国际研究经验
批准号:
2106416
负责人:
Yiyu Shi
金额:
$30.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-11-01 至 2024-10-31

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中文摘要
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英文摘要
The objective of this IRES project is to provide U.S. students with valuable research experience in the exploration of novel artificial intelligence (AI) algorithms for congenital heart diseases (CHDs) in Guangdong Provincial Cardiovascular Institute (GCI), located at Guangdong General Hospital (GGH). Located in Guangzhou, China, GGH is one of the biggest hospitals in China, and the GCI affiliated with it is constantly ranked top three in terms of cardiovascular disease research. The project will select three (3) graduate students and three (3) undergraduate students nation-wide each year and support them to visit GCI over a period of twelve (12) weeks to work with world-renowned researchers on cardiovascular medicine in an immersive setting, addressing some of the most critical and challenging problems through innovative AI algorithms that can benefit the large population suffering from CHD.CHD is the leading cause of mortality from birth defects, which occurs 1 in every 110 births in the United States, and even more in developing countries. CHD comes with very large structure variations which makes it time-consuming and tedious to diagnose manually. In addition, the most common treatment for CHD is cardiac surgery, which is rather complex and is widely regarded as the jewel in the crown of surgery. Currently, only radiologists and surgeons with extensive experience in CHD can handle them confidently. The outcome of this project will potentially boost the effectiveness and efficiency of CHD treatments, and benefit the large population worldwide who suffer from CHD. The project will also enable U.S. students to conduct high-quality research on AI for CHD, in collaboration with their research mentors at GCI. Such experiences expose them to the international research community at a critical early stage in their careers. It is expected that through participating in this program, U.S. students will gain extensive experience on the research of deep learning with medical applications, on the international healthcare prospects, on Chinese culture, and on performing and collaborating in an international environment in general. The experience will also be shared to the broader community through personal social media as well as outreach events such as KidAI webinars for national K-12 students interested in AI. To ensure sustainability, the project will provide professional development support for the participating students. It will also focus on minorities and underrepresented groups.The scientific objective of this IRES project is to explore innovative AI algorithms that can benefit the diagnosis, treatment planning and prognosis of CHDs. The proposed research, through the collaborationbetween doctors at GCI and the IRES visiting students in the engineering fields, targets fundamentalissues in medical image processing and diagnosis of CHD that need to be addressed urgently. Although AI has shown great potential in general medicine, the large heart structure and great vessel connection variations in CHDs cannot be handled well by existing AI algorithms developed for other diseases. The proposed research will be the first to tackle this challenge and innovative algorithms are expected to be developed. It can also be anticipated that with the close interaction with leading research group on cardiovascular diseases in China, the breakthroughs made from these projects at GCI can have a direct impact on AI-based medicine research, clinic usage, and social welfare.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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