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SCH: Robust Multimodal Longitudinal AI for Enhanced Breast Cancer Screening is sponsored by National Cancer Institute (NCI) / NIH. This project aims to optimize and personalize breast cancer screening by advancing AI algorithms. It proposes a more realistic AI-CAD system that mimics a radiologist's approach by comparing current and prior mammograms, incorporating clinical risk factors, and accounting for image configuration variations.
It also focuses on practical implementation for clinical use, ensuring model adaptivity and computational feasibility, and will provide a comprehensive DBT database for training, evaluating, and validating models.
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Or search similar grants →According to the current listing, eligibility includes: Awardee organization is the University of Connecticut Storrs. This indicates that universities and research institutions are eligible. Confirm the full requirements in the official notice before applying.
Applications for SCH: Robust Multimodal Longitudinal AI for Enhanced Breast Cancer Screening are due July 31, 2028. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
SCH: Robust Multimodal Longitudinal AI for Enhanced Breast Cancer Screening is funded by National Cancer Institute (NCI) / NIH. Verify program details on the funder's official page before applying.
This opportunity targets applicants in Connecticut. If your organization operates elsewhere, check the official notice for location requirements.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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