{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T17:40:27Z","timestamp":1775842827795,"version":"3.50.1"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R21CA225175"],"award-info":[{"award-number":["R21CA225175"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P41EB017183"],"award-info":[{"award-number":["P41EB017183"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1109\/tmi.2019.2945514","type":"journal-article","created":{"date-parts":[[2019,10,7]],"date-time":"2019-10-07T20:03:32Z","timestamp":1570478612000},"page":"1184-1194","source":"Crossref","is-referenced-by-count":523,"title":["Deep Neural Networks Improve Radiologists\u2019 Performance in Breast Cancer Screening"],"prefix":"10.1109","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4953-5933","authenticated-orcid":false,"given":"Nan","family":"Wu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3522-1869","authenticated-orcid":false,"given":"Jason","family":"Phang","sequence":"additional","affiliation":[]},{"given":"Jungkyu","family":"Park","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7726-2514","authenticated-orcid":false,"given":"Yiqiu","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Zhe","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Masha","family":"Zorin","sequence":"additional","affiliation":[]},{"given":"Stanislaw","family":"Jastrzebski","sequence":"additional","affiliation":[]},{"given":"Thibault","family":"Fevry","sequence":"additional","affiliation":[]},{"given":"Joe","family":"Katsnelson","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5242-0291","authenticated-orcid":false,"given":"Eric","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Stacey","family":"Wolfson","sequence":"additional","affiliation":[]},{"given":"Ujas","family":"Parikh","sequence":"additional","affiliation":[]},{"given":"Sushma","family":"Gaddam","sequence":"additional","affiliation":[]},{"given":"Leng Leng Young","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Kara","family":"Ho","sequence":"additional","affiliation":[]},{"given":"Joshua D.","family":"Weinstein","sequence":"additional","affiliation":[]},{"given":"Beatriu","family":"Reig","sequence":"additional","affiliation":[]},{"given":"Yiming","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Hildegard","family":"Toth","sequence":"additional","affiliation":[]},{"given":"Kristine","family":"Pysarenko","sequence":"additional","affiliation":[]},{"given":"Alana","family":"Lewin","sequence":"additional","affiliation":[]},{"given":"Jiyon","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Krystal","family":"Airola","sequence":"additional","affiliation":[]},{"given":"Eralda","family":"Mema","sequence":"additional","affiliation":[]},{"given":"Stephanie","family":"Chung","sequence":"additional","affiliation":[]},{"given":"Esther","family":"Hwang","sequence":"additional","affiliation":[]},{"given":"Naziya","family":"Samreen","sequence":"additional","affiliation":[]},{"given":"S. Gene","family":"Kim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0900-0459","authenticated-orcid":false,"given":"Laura","family":"Heacock","sequence":"additional","affiliation":[]},{"given":"Linda","family":"Moy","sequence":"additional","affiliation":[]},{"given":"Kyunghyun","family":"Cho","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0549-1446","authenticated-orcid":false,"given":"Krzysztof J.","family":"Geras","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"crossref","DOI":"10.1007\/978-94-011-5318-8_75","article-title":"Current status of the digital database for screening mammography","author":"heath","year":"1998","journal-title":"Digital Mammography"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2011.09.014"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.18.20392"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-017-9993-2"},{"key":"ref31","article-title":"End-to-end training for whole image breast cancer diagnosis using an all convolutional design","author":"shen","year":"2017","journal-title":"arXiv 1711 05775"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.07.007"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2018181371"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djy222"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000000358"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s12609-019-0301-7"},{"key":"ref10","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"Proc ICLR"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref13","article-title":"The NYU breast cancer screening dataset V1.0","author":"wu","year":"2019"},{"key":"ref14","article-title":"High-resolution breast cancer screening with multi-view deep convolutional neural networks","author":"geras","year":"2017","journal-title":"arXiv 1703 07047"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8462671"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007379606734"},{"key":"ref17","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc ICLR"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2017.59"},{"key":"ref19","first-page":"169","article-title":"A multi-scale CNN and curriculum learning strategy for mammogram classification","author":"lotter","year":"2017","journal-title":"Proc DLMIA"},{"key":"ref28","first-page":"603","article-title":"Deep multi-instance networks with sparse label assignment for whole mammogram classification","author":"zhu","year":"2017","journal-title":"Proc MICCAI"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3322\/canjclin.52.2.68"},{"key":"ref27","article-title":"Applying data-driven imaging biomarker in mammography for breast cancer screening: Preliminary study","volume":"8","author":"kim","year":"2018","journal-title":"Sci Rep"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.10220"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2015.5231"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.4.4.044501"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-015-3373-8"},{"key":"ref8","first-page":"396","article-title":"Handwritten digit recognition with a back-propagation network","author":"lecun","year":"1989","journal-title":"Proc NIPS"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.10765"},{"key":"ref9","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc NIPS"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21254"},{"key":"ref20","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-018-22437-z","article-title":"Detecting and classifying lesions in mammograms with deep learning","volume":"8","author":"ribli","year":"2018","journal-title":"Sci Rep"},{"key":"ref22","article-title":"The unreasonable effectiveness of noisy data for fine-grained recognition","author":"krause","year":"2015","journal-title":"arXiv 1511 06789"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref24","doi-asserted-by":"crossref","DOI":"10.1007\/3-540-45014-9_1","article-title":"Ensemble methods in machine learning","author":"dietterich","year":"2000","journal-title":"Multiple Classifier Systems"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.97"},{"key":"ref26","article-title":"MAMMO: A deep learning solution for facilitating radiologist-machine collaboration in breast cancer diagnosis","author":"kyono","year":"2018","journal-title":"arXiv 1811 02661"},{"key":"ref25","article-title":"Umap: Uniform manifold approximation and projection for dimension reduction","author":"mcinnes","year":"2018","journal-title":"arXiv 1802 03426"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/42\/9055242\/8861376-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/9055242\/08861376.pdf?arnumber=8861376","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T18:47:29Z","timestamp":1649443649000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8861376\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":39,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2019.2945514","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4]]}}}