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

Grant Number Project Title Principal Investigator Institution
5-R01-EB029957-04 A comprehensive deep learning framework for MRI reconstruction Rizwan Ahmad Ohio State University
5-R01-EB031585-04 A Computational Framework Enabling Virtual Imaging Trials of 3D Quantitative Optoacoustic Tomography Breast Imaging Mark Anastasio University of Illinois at Urbana-Champaign
5-R01-EB032716-04 Adversarially Based Virtual CT Workflow for Evaluation of AI in Medical Imaging Ge Wang Rensselaer Polytechnic Institute
1-R01-EB036987-01 AI-assisted quantitative photon-counting-detector CT imaging for cytogenetic risk prediction and treatment response in multiple myeloma Francis Baffour Mayo Clinic Rochester
5-R01-EB032807-03 AI-based Cardiac CT Hengyong Yu University of Massachusetts Lowell
1-R21-EB037268-01 AI-driven hip exoskeleton control framework that rapidly generalizes to a broad range of users and real-world locomotor tasks Inseung Kang Carnegie-Mellon University
1-R01-EB035679-01A1 An AI-Assisted Strategy for Monitoring Pulmonary Congestion in Acute Heart Failure Patients in Emergency Settings Tina Kapur Brigham And Women'S Hospital
1-R01-EB036877-01 An Artificial Intelligence Coaching System to Improve Surgical Performance in Urologic Endoscopy Roger Daglius Dias Brigham And Women'S Hospital
5-R21-EB030677-02 Automated Sonographic Detection of Pulmonary Embolism Using Machine Learning Algorithm Srikar Adhikari University of Arizona
5-P41-EB031772-03 Center for Label-free Imaging and Multiscale Biophotonics (CLIMB) Stephen Boppart University of Illinois at Urbana-Champaign