High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision

Radiology, 2017, Pages 170549-170549.

Cited by: 11|Bibtex|Views12|
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Other Links: pubmed.ncbi.nlm.nih.gov|academic.microsoft.com

Abstract:

Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs) diagnosed with image-guided needle biopsy that require surgical excision to be distinguished from HRLs that are at low risk for upgrade to cancer at surgery and thus could be surveilled. Materials and Methods Consecutive patients with biopsy-proven HRL...More

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