A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images-Reference-Cited by-同舟云学术

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A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images

Published:2021-08-16 Issue:8 Volume:4 Page:e2119100
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Buda Mateusz¹,Saha Ashirbani¹,Walsh Ruth¹,Ghate Sujata¹,Li Nianyi¹,Swiecicki Albert¹,Lo Joseph Y.¹²,Mazurowski Maciej A.¹²³⁴

Affiliation:

1. Department of Radiology, Duke University Medical Center, Durham, North Carolina

2. Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina

3. Department of Computer Science, Duke University, Durham, North Carolina

4. Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2783046/buda_2021_oi_210568_1628278929.17056.pdf

Reference26 articles.

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2. Artificial intelligence in breast imaging.;Le;Clin Radiol,2019

3. Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms.;Schaffter;JAMA Netw Open,2020

4. Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study.;Kim;Lancet Digit Health,2020

5. International evaluation of an AI system for breast cancer screening.;McKinney;Nature,2020

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