Funded Projects for Artificial Intelligence, Machine Learning, and Deep Learning | National Institute of Biomedical Imaging and Bioengineering

Grant Number	Project Title	Principal Investigator	Institution
5-R01-EB017095-11	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-EB033994-03	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.
1-R01-EB031872-01	FluoRender: Rapid Quantitative Analysis and Adaptive Workflows for Fluorescence Microscopy Data in Fundamental Biomedical Research	Charles Hansen	University of Utah
1-R21-EB035247-01A1	Improving prognosis prediction and therapy selection for cutaneous squamous cell carcinomas using artificial intelligence	William Lotter	Dana-Farber Cancer Inst
5-R01-EB029699-04	Intelligent Intensive Care Unit (I2CU): Pervasive Sensing and Artificial Intelligence for Augmented Clinical Decision-making	Parisa Rashidi	University of Florida
1-F31-EB035931-01A1	Interpretable Real-Time Surgical Skill Assessment Via Optical Neuroimaging	Condell Eastmond	Rensselaer Polytechnic Institute
1-R21-EB030294-01A1	Machine learning approach to non-invasive MRI-based blood oximetry	Juliet Varghese	Ohio State University
4-R00-EB033857-03	Machine Learning-enabled Classification of Extracellular Vesicles Using Nanoplasmonic Microfluidics	Colin Hisey	Northwestern University
5-R01-EB033788-03	Maternal mHealth blood hemoglobin analysis with informed deep learning	Young Kim	Purdue University