The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to implement an artificial intelligence (AI) method to assess COVID-19 in medical images, including diagnosis of the disease, prediction of disease severity, and measurement of treatment response. Given the ongoing COVID-19 pandemic, the primary aim of this proposal is to support frontline clinicians and researchers in caring for patients and developing effective therapies. Imaging is a critical but still underdeveloped component of COVID-19 patient care. This project will advance the understanding of COVID-19 imaging practices, utilizing best practices for training, validating, and deploying artificial intelligence applications. In addition, the imaging AI platform developed for creating COVID-19 algorithms will be broadly useful for a wide range of other radiology applications.
This Small Business Innovation Research (SBIR) Phase I project aims to implement a platform that is uniquely positioned to enable full cycle development, validation, deployment, and ongoing tuning of imaging AI algorithms to improve the care of COVID-19 patients. Technical tasks include: developing methods to aggregate clinical and imaging data from diverse hospital information systems, implementing services and user interfaces to conduct federated learning experiments securely across remote data and computational systems, and developing mechanisms to publish and subscribe to validated high quality AI models for deployment in clinical environments. The core platform is already operational in many large academic medical centers, so translation will be straightforward.
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.
