Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms-Reference-Cited by-同舟云学术

Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms

Published:2019-08 Issue:2 Volume:292 Page:331-342
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Akselrod-Ballin Ayelet¹,Chorev Michal¹^ORCID,Shoshan Yoel¹^ORCID,Spiro Adam¹^ORCID,Hazan Alon¹^ORCID,Melamed Roie¹^ORCID,Barkan Ella¹^ORCID,Herzel Esma¹^ORCID,Naor Shaked¹^ORCID,Karavani Ehud¹^ORCID,Koren Gideon¹^ORCID,Goldschmidt Yaara¹^ORCID,Shalev Varda¹^ORCID,Rosen-Zvi Michal¹^ORCID,Guindy Michal¹^ORCID

Affiliation:

1. From the Department of Healthcare Informatics, IBM Research, IBM R&D Labs, University of Haifa Campus, Mount Carmel, Haifa 3498825, Israel (A.A.B., M.C., Y.S., A.S., A.H., R.M., E.B., S.N., E.K., Y.G., M.R.Z.); MaccabiTech, MKM, Maccabi Healthcare Services, Tel Aviv, Israel (E.H., G.K., V.S.); and Department of Imaging, Assuta Medical Centers, Tel Aviv, Israel (M.G.).

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2019182622

Reference33 articles.

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4. Sickles EA, D’Orsi CJ, Bassett LW. American College of Radiology Breast Imaging Reporting and Data System Atlas (ACR BI-RADS Atlas). Reston, Va: American College of Radiology, 2013.

5. Beyond mammography screening: quality assurance in breast cancer diagnosis (The QuaMaDi Project)

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