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Funded Projects for Artificial Intelligence, Machine Learning, and Deep Learning

Grant Number Project Title Principal Investigator Institution
1-R01-EB035186-01A1 DeepTOBIDx: deep learning-enhanced multimodal diagnostic breast imaging Bin Deng Massachusetts General Hospital
5-R21-EB029493-03 Development of quantitative tools to predict patients with difficult intubation to minimize treatment related complications Muhammad Khalid Khan Niazi Wake Forest University Health Sciences
5-R01-EB030130-03 Development of Software to Rapidly Assess Placenta Images at Birth Alison Gernand Pennsylvania State University, The
2-R01-EB017095-10 Diagnostic performance assessment and dose optimization using patient CT images: Application to deep-learning CT reconstruction and denoising technologies Cynthia Mccollough Mayo Clinic Rochester
5-R21-EB033426-02 DL-based CT image formation with characterization and control of resolution and noise Jingyan Xu Johns Hopkins University
5-R21-EB033994-02 Early-Stage Clinical Trial of AI-Driven CBCT-Guided Adaptive Radiotherapy for Lung Cancer Aparna Kesarwala Emory University
5-R44-EB032722-03 Enabling Next Generation Machine Learning for Large Scale Image Analysis Gerald Sabin Rnet Technologies, Inc.
5-R21-EB032187-03 Enhanced Clinical Diagnosis through Imaging and Modeling: A Machine Learning Data Fusion Framework Hessam Babaee University of Pittsburgh at Pittsburgh
1-R01-EB031872-01 FluoRender: Rapid Quantitative Analysis and Adaptive Workflows for Fluorescence Microscopy Data in Fundamental Biomedical Research Charles Hansen University of Utah
5-R01-EB031575-03 Harmonization of breast MRI data Maciej Mazurowski Duke University