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

Grant Number Project Title Principal Investigator Institution
1-R01-EB036579-01A1 Pragmatic and automated pressure injury detection across a heterogeneous patient population Sharon Sonenblum Emory University
1-R21-EB034428-01A1 Predicting recovery after TBI: Development and comparison of MR-supplemented models using non-parametric and machine learning multimodal fusion Martin Monti University of California Los Angeles
2-R01-EB020683-05A1 Quantitative imaging and molecular data modeling for brain tumor recurrence and progression analysis Khan Iftekharuddin Old Dominion University
1-R01-EB036013-01A1 Resolution Enhancement and Contrast Harmonization for MR Neuroimaging Jerry Prince Johns Hopkins University
1-R01-EB037101-01 Robust and Interpretable Multi-modal AI/ML for Precision Medicine Tianlong Chen Univ of North Carolina Chapel Hill
1-R01-EB038719-01 SCH: Interpretable Machine Learning and Discovery in Medical Images Cynthia Rudin Duke University
5-R01-EB032896-04 SCH: Leverage clinical knowledge to augment deep learning analysis of breast images Shandong Wu University of Pittsburgh at Pittsburgh
7-R01-EB034116-03 SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate Heng Huang Univ of Maryland, College Park
1-R01-EB038734-01 SCH: Technology for Personalized Surgical Feedback using Vision and Language Data. Satyanarayana Vedula Johns Hopkins University
5-R01-EB021391-08 Shape Analysis Toolbox: From medical images to quantitative insights of anatomy Beatriz Paniagua Kitware, Inc.