The promise of AI in personalized breast cancer screening: are we there yet?
Author:
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41571-024-00877-z.pdf
Reference10 articles.
1. Yala, A. et al. Multi-institutional validation of a mammography-based breast cancer risk model. J. Clin. Oncol. 40, 1732–1740 (2022).
2. Lehman, C. D. et al. Diagnostic accuracy of digital screening mammography with and without computer-aided detection. JAMA Intern. Med. 175, 1828–1837 (2015).
3. Nishikawa, R. M., Schmidt, R. A. & Metz, C. E. Computer-aided screening mammography. N. Engl. J. Med. 357, 84 (2007).
4. Lång, K. et al. Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study. Lancet Oncol. 24, 936–944 (2023).
5. Yala, A., Lehman, C., Schuster, T., Portnoi, T. & Barzilay, R. A deep learning mammography-based model for improved breast cancer risk prediction. Radiology 292, 60–66 (2019).
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