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

Grant Number Project Title Principal Investigator Institution
2-R01-EB022573-09 Interpretable Deep Learning for Analyzing Brain Development Heterogeneity with Personalized Functional Networks Across Multi-Site Data Yong Fan University of Pennsylvania
1-F31-EB035931-01A1 Interpretable Real-Time Surgical Skill Assessment Via Optical Neuroimaging Condell Eastmond Rensselaer Polytechnic Institute
7-R21-EB033455-04 Knowledge-informed Deep Learning for Apnea Detection with Limited Annotations Xiaochen Xian Georgia Institute of Technology
1-R01-EB036530-01A1 Leveraging Multi-Modal AI for Selective Use of Ultrasound in Breast Cancer Screening Yiqiu Shen New York University School of Medicine
5-R00-EB033857-04 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
1-R13-EB038076-01 Medical Imaging with Deep Learning (MIDL) Conference 2025 Tolga Tasdizen University of Utah
1-R21-EB036734-01A1 Multimodality and Longitudinal Artificial Intelligence for Diagnosis and Prognosis in Hepatic Steatosis Walter Witschey University of Pennsylvania
5-K25-EB035166-02 New Tools for Enhancing Cerebral Angiography: From Planning to Navigation Nazim Haouchine Brigham And Women'S Hospital
5-R01-EB031032-04 Non-invasive automated wound analysis via deep learning neural networks Kyle Quinn University of Arkansas at Fayetteville