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

Grant Number Project Title Principal Investigator Institution
1-R01-EB035934-01 XAI-TRUST: Explainable AI Techniques to Rigorously Understand, Scrutinize, and Trust Clinical AI Su-In Lee University of Washington
5-R01-EB034737-02 Unsupervised Deep Photon-Counting Computed Tomography Reconstruction for Human Extremity Imaging Hengyong Yu University of Massachusetts Lowell
5-R01-EB001838-16 Simulation Tools for 3D and 4D CT and Dosimetry William Segars Duke University
5-R01-EB021391-08 Shape Analysis Toolbox: From medical images to quantitative insights of anatomy Beatriz Paniagua Kitware, Inc.
7-R01-EB034116-03 SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate Heng Huang Univ of Maryland, College Park
5-R01-EB032896-04 SCH: Leverage clinical knowledge to augment deep learning analysis of breast images Shandong Wu University of Pittsburgh at Pittsburgh
5-R01-EB030582-04 Quantification of Liver Fibrosis with MRI and Deep Learning Lili He Cincinnati Childrens Hosp Med Ctr
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
5-R01-EB022573-08 Personalized Functional Network Modeling to Characterize and Predict Psychopathology in Youth Yong Fan University of Pennsylvania
1-R01-EB035394-01A1 Optimizing Mobile Photon-Counting CT Image Quality via Deep Learning for Neuro Intensive Care Unit Dufan Wu Massachusetts General Hospital