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Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening

Please click the image to view the full paper. ➥

Reference:
Sarah S. Aboutalib, Aly A. Mohamed, Wendie A. Berg, Margarita L. Zuley, Jules H. Sumkin and Shandong Wu, "Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening," Clinical Cancer Research, Oct 2018.
http://clincancerres.aacrjournals.org/content/early/2018/09/26/1078-0432.CCR-18-1115


AACR newsroom:
https://www.aacr.org/Newsroom/Pages/News-Release-Detail.aspx?ItemID=1231

Other media coverage:
https://www.auntminnie.com/index.aspx?sec=ser&sub=def&pag=dis&ItemID=122130
https://www.eurekalert.org/pub_releases/2018-10/aafc-dlc100918.php
https://www.news-medical.net/news/20181011/AI-approach-could-identify-nuanced-imaging-features-specific-for-recalled-benign-mammograms.aspx
https://www.healthimaging.com/topics/artificial-intelligence/ai-distinguish-between-false-positive-malignant-negative-mammograms
https://www.radiologybusiness.com/topics/artificial-intelligence/ai-false-positive-mammogram-malignant-negative-results
https://www.technologynetworks.com/informatics/news/deep-learning-catches-out-false-positive-mammograms-310587
https://blog.aacr.org/can-artificial-intelligence-help-reduce-false-positive-mammograms/

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Address: Radiology Administration
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