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Radiology|February 25, 2025
Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language ModelsDavid B Larson, Arogya Koirala, Lina Y Cheuy, et al.
Learning Health Systems|October 20, 2022
Evaluating clinician-led quality improvement initiatives: A system-wide embedded research partnership at Stanford MedicineStacie Vilendrer, Erika A Saliba-Gustafsson, Steven M Asch, et al.
Radiology|November 15, 2017
Deep Learning to Classify Radiology Free-Text ReportsMatthew C Chen, Robyn L Ball, Lingyao Yang, et al.
Radiographics : a Review Publication of the Radiological Society of North America, Inc|November 1, 2021
Increasing the Utilization of Moderate Sedation Services for Pediatric ImagingEvan J Zucker, Stephanie Wintch, Young Chang, et al.
Journal of Magnetic Resonance Imaging : JMRI|August 25, 2020
Prospective Deployment of Deep Learning in MRI: A Framework for Important Considerations, Challenges, and Recommendations for Best PracticesAkshay S Chaudhari, Christopher M Sandino, Elizabeth K Cole, et al.
Radiographics : a Review Publication of the Radiological Society of North America, Inc|December 4, 2025
Improving Prostate MRI: Lessons Learned from the American College of Radiology's Prostate MR Image Quality Improvement CollaborativeAndrei S Purysko, Kandice Garcia-Tomkins, Kay Zacharias-Andrews, et al.
Journal of the American College of Radiology : JACR|December 30, 2008
RADPEER scoring white paperValerie P Jackson, Trudie Cushing, Hani H Abujudeh, et al.
Mayo Clinic Proceedings. Digital Health|January 13, 2025
Developing a Research Center for Artificial Intelligence in MedicineCurtis P Langlotz, Johanna Kim, Nigam Shah, et al.
Journal of the American College of Radiology : JACR|December 11, 2025
The ACR Medical Image Quality Assessment System (MIQAS): A Unified Approach to Image Quality Assessment in RadiologyDavid B Larson, Ella A Kazerooni, Ben C Wandtke, et al.
Research Square|June 12, 2025
Automated Real-time Assessment of Intracranial Hemorrhage Detection AI Using an Ensembled Monitoring Model (EMM)Zhongnan Fang, Andrew Johnston, Lina Cheuy, et al.
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