I-Corps: Translation Potential of a Platform for Medical Artificial Intelligence (AI) Model Development and Sharing
- Institution
- Icahn School of Medicine at Mount Sinai, NY
- Principal investigator
- Xueyan Mei
- Funding
- $50K
- Duration
- 2025–2026
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Abstract
This I-Corps project is based on the lab to market translation of an open-source web application that allows doctors and researchers to share digital resources and accelerate the development of artificial intelligence (AI) models in medicine. Although AI in medicine is rapidly advancing, current approaches face challenges such as limited data sharing and restricted access to models, hindering its widespread adoption in medical research settings. This solution addresses these issues by creating a collaborative space for doctors and researchers to develop, share, and refine medical AI models. By fostering an open and cooperative environment, this project seeks to make advanced AI tools more widely accessible, helping to develop more robust, adaptable, and impactful medical AI solutions for medical research. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a digital platform to create a collaborative space for healthcare professionals and researchers to work together towards the development and deployment of cutting-edge medical artificial intelligence (AI) tools for use in medical research. The benefits of this approach include interactive medical data viewers, an open-source medical model hub, and a code-free development space, all designed to streamline the creation and deployment of advanced medical research-related AI models. Furthermore, by facilitating accessibility to AI-powered medical research solutions, this technology has the potential to accelerate new discoveries in data-intensive fields of medicine and clinical care, such as personalized medicine and digital twin technologies. 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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