Multi-magnification-based machine learning as an ancillary tool for the pathologic assessment of shaved margins for breast carcinoma lumpectomy specimens-Reference-Cited by-同舟云学术

Multi-magnification-based machine learning as an ancillary tool for the pathologic assessment of shaved margins for breast carcinoma lumpectomy specimens

Published:2021-04-26 Issue:8 Volume:34 Page:1487-1494
ISSN:0893-3952
Container-title:Modern Pathology
language:en
Short-container-title:Mod Pathol

Author:

D’Alfonso Timothy M.^ORCID,Ho David Joon^ORCID,Hanna Matthew G.,Grabenstetter Anne^ORCID,Yarlagadda Dig Vijay Kumar,Geneslaw Luke^ORCID,Ntiamoah Peter,Fuchs Thomas J.,Tan Lee K.

Publisher

Springer Science and Business Media LLC

Subject

Pathology and Forensic Medicine

Link

http://www.nature.com/articles/s41379-021-00807-9.pdf

Reference22 articles.

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3. Marinovich ML, Azizi L, Macaskill P, Irwig L, Morrow M, Solin LJ, et al. The association of surgical margins and local recurrence in women with ductal carcinoma in situ treated with breast-conserving therapy: a meta-analysis. Ann Surg Oncol. 2016;23:3811–21.

4. Molina MA, Snell S, Franceschi D, Jorda M, Gomez C, Moffat FL, et al. Breast specimen orientation. Ann Surg Oncol. 2009;16:285–8.

5. Wright MJ, Park J, Fey JV, Park A, O’Neill A, Tan LK, et al. Perpendicular inked versus tangential shaved margins in breast-conserving surgery: does the method matter? J Am Coll Surg. 2007;204:541–9.

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