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

Grant Number Project Title Principal Investigator Institution
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
5-R21-EB033455-03 Knowledge-informed Deep Learning for Apnea Detection with Limited Annotations Xiaochen Xian University of Florida
1-R21-EB030294-01A1 Machine learning approach to non-invasive MRI-based blood oximetry Juliet Varghese Ohio State University
5-R21-EB030762-02 Machine Learning-Based Adaptation of Data Sampling and Reconstruction for Efficient Dynamic MRI Saiprasad Ravishankar Michigan State University
5-K99-EB033857-02 Machine Learning-enabled Classification of Extracellular Vesicles Using Nanoplasmonic Microfluidics Colin Hisey Ohio State University
4-R00-EB033857-03 Machine Learning-enabled Classification of Extracellular Vesicles Using Nanoplasmonic Microfluidics Colin Hisey Northwestern University
5-R01-EB033788-02 Maternal mHealth blood hemoglobin analysis with informed deep learning Young Kim Purdue University
5-R01-EB029944-04 MRI and Deep Learning for Early Prediction of Neurodevelopmental Deficits in Very Preterm Infants Lili He Cincinnati Childrens Hosp Med Ctr
1-K25-EB035166-01 New Tools for Enhancing Cerebral Angiography: From Planning to Navigation Nazim Haouchine Brigham And Women'S Hospital