Advancing Artificial Intelligence to Meet Breast Imaging Needs
Author:
Affiliation:
1. From the Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520.
Publisher
Radiological Society of North America (RSNA)
Subject
Radiology, Nuclear Medicine and imaging
Link
http://pubs.rsna.org/doi/pdf/10.1148/radiol.213101
Reference9 articles.
1. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis
2. Can Computer-aided Detection Be Detrimental to Mammographic Interpretation?
3. Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection
4. Artificial intelligence in breast imaging
5. AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation
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