| 1-DP2-EB035858-01 |
Crowd-Powered Machine Learning to Diagnose ASD and ADHD in Adolescents from Digital Social Interactions |
Peter Washington |
University of Hawaii at Manoa |
| 1-K25-EB035166-01 |
New Tools for Enhancing Cerebral Angiography: From Planning to Navigation |
Nazim Haouchine |
Brigham And Women'S Hospital |
| 1-R01-EB031102-01 |
Constrained Disentanglement (CODE) Network for CT Metal Artifact Reduction in Radiation Therapy |
Ge Wang |
Rensselaer Polytechnic Institute |
| 1-R01-EB034249-01 |
Deep learning technologies for estimating the optimal task performance of medical imaging systems |
Mark Anastasio |
University of Illinois at Urbana-Champaign |
| 1-R01-EB035934-01 |
XAI-TRUST: Explainable AI Techniques to Rigorously Understand, Scrutinize, and Trust Clinical AI |
Su-In Lee |
University of Washington |
| 1-R21-EB029607-01A1 |
Decoding inner speech: An AI approach to transcribing thoughts via EEG & EMG |
Jose Cortes-Briones |
Yale University |
| 1-R21-EB029627-01 |
Machine learning for fast motion compensated quantitative abdominal DCE-MRI |
Sila Kurugol |
Boston Children'S Hospital |
| 1-R21-EB030294-01A1 |
Machine learning approach to non-invasive MRI-based blood oximetry |
Juliet Varghese |
Ohio State University |
| 1-R21-EB030677-01A1 |
Automated Sonographic Detection of Pulmonary Embolism Using Machine Learning Algorithm |
Srikar Adhikari |
University of Arizona |
| 1-R21-EB031939-01 |
Dual Energy CT-enabled Asymptomatic Pulmonary Embolism Detection on Non-contrast CT |
Dufan Wu |
Massachusetts General Hospital |
