AI-driven Selection of Candidates for Supplemental Breast Cancer Screening-Reference-Cited by-同舟云学术

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AI-driven Selection of Candidates for Supplemental Breast Cancer Screening

Published:2024-04-01 Issue:1 Volume:311 Page:
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Kim Myoung Kyoung¹^ORCID,Chang Jung Min¹^ORCID

Affiliation:

1. From the Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea (M.K.K.); Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea (J.M.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea (J.M.C.).

Publisher

Radiological Society of North America (RSNA)

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.240447

Reference10 articles.

1. Detection of Breast Cancer With Addition of Annual Screening Ultrasound or a Single Screening MRI to Mammography in Women With Elevated Breast Cancer Risk

2. Sensitivity and specificity of mammography and adjunctive ultrasonography to screen for breast cancer in the Japan Strategic Anti-cancer Randomized Trial (J-START): a randomised controlled trial

3. Supplemental MRI Screening for Women with Extremely Dense Breast Tissue

4. Breast Cancer Screening for Women at Higher-Than-Average Risk: Updated Recommendations From the ACR

5. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction

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