{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T22:04:38Z","timestamp":1790633078733,"version":"4.1.0"},"reference-count":15,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T00:00:00Z","timestamp":1721865600000},"content-version":"am","delay-in-days":328,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","ejradiology.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["European Journal of Radiology"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1016\/j.ejrad.2023.111002","type":"journal-article","created":{"date-parts":[[2023,7,22]],"date-time":"2023-07-22T19:23:01Z","timestamp":1690053781000},"page":"111002","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":6,"special_numbering":"C","title":["Deep learning-based automatic detection for pulmonary nodules on chest radiographs: The relationship with background lung condition, nodule characteristics, and location"],"prefix":"10.1016","volume":"166","author":[{"given":"Midori","family":"Ueno","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kotaro","family":"Yoshida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atsushi","family":"Takamatsu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takeshi","family":"Kobayashi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takatoshi","family":"Aoki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshifumi","family":"Gabata","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ejrad.2023.111002_b0005","doi-asserted-by":"crossref","first-page":"1818","DOI":"10.1007\/s00330-008-0948-3","article-title":"Digital chest radiography: an update on modern technology, dose containment and control of image quality","volume":"18","author":"Schaefer-Prokop","year":"2008","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.ejrad.2023.111002_b0010","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/S0720-048X(01)00301-1","article-title":"Detection of lung cancer on the chest radiograph: a study on observer performance","volume":"39","author":"Quekel","year":"2001","journal-title":"Eur. J. Radiol."},{"key":"10.1016\/j.ejrad.2023.111002_b0015","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1056\/NEJMoa1208962","article-title":"Results of the two incidence screenings in the national lung screening trial","volume":"369","author":"Aberle","year":"2013","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.ejrad.2023.111002_b0020","doi-asserted-by":"crossref","first-page":"564","DOI":"10.3348\/kjr.2012.13.5.564","article-title":"Computer-aided detection of malignant lung nodules on chest radiographs: Effect on observers\u2019 performance","volume":"13","author":"Lee","year":"2012","journal-title":"Korean J. Radiol."},{"key":"10.1016\/j.ejrad.2023.111002_b0025","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1148\/radiol.2018180237","article-title":"Development and validation of deep learning-based automatic detection algorithm for malignant pulmonary nodules on chest radiographs","volume":"290","author":"Nam","year":"2019","journal-title":"Radiology"},{"key":"10.1016\/j.ejrad.2023.111002_b0030","doi-asserted-by":"crossref","unstructured":"M.L. Giger, K. Doi, H. MacMahon, Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields, Med. Phys. 15 (1988) 158\u2013166, doi: 10.1118\/1.596247.","DOI":"10.1118\/1.596247"},{"key":"10.1016\/j.ejrad.2023.111002_b0035","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1186\/s12885-021-08847-9","article-title":"Artificial intelligence-supported lung cancer detection by multi-institutional readers with multi-vendor chest radiographs: A retrospective clinical validation study","volume":"21","author":"Ueda","year":"2021","journal-title":"BMC Cancer"},{"key":"10.1016\/j.ejrad.2023.111002_b0040","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1148\/radiol.2020200165","article-title":"Deep learning-based automatic detection algorithm for reducing overlooked lung cancers on chest radiographs","volume":"296","author":"Jang","year":"2020","journal-title":"Radiology"},{"key":"10.1016\/j.ejrad.2023.111002_b0045","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.221894","article-title":"AI improves nodule detection on chest radiographs in a health screening population: a randomized controlled trial","volume":"307","author":"Nam","year":"2023","journal-title":"Radiology"},{"key":"10.1016\/j.ejrad.2023.111002_b0050","doi-asserted-by":"crossref","first-page":"9664","DOI":"10.1007\/s00330-021-08074-7","article-title":"AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset","volume":"31","author":"Yoo","year":"2021","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.ejrad.2023.111002_b0055","doi-asserted-by":"crossref","first-page":"1507","DOI":"10.1016\/j.acra.2011.08.008","article-title":"Computer-aided detection of small pulmonary nodules in chest radiographs: an observer study","volume":"18","author":"De Boo","year":"2011","journal-title":"Acad. Radiol."},{"key":"10.1016\/j.ejrad.2023.111002_b0060","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1148\/radiol.2016150063","article-title":"Low-dose CT screening for lung cancer: computer-aided detection of missed lung cancers","volume":"281","author":"Liang","year":"2016","journal-title":"Radiology"},{"key":"10.1016\/j.ejrad.2023.111002_b0065","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1016\/S0009-9260(98)80312-7","article-title":"Imaging the 'dirty lung': has high-resolution computed tomography cleared the smoke?","volume":"53","author":"Geckel","year":"1998","journal-title":"Clin. Radiol."},{"key":"10.1016\/j.ejrad.2023.111002_b0070","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1148\/radiol.2462070712","article-title":"Fleischner society: glossary of terms for thoracic imaging","volume":"246","author":"Hansell","year":"2008","journal-title":"Radiology"},{"key":"10.1016\/j.ejrad.2023.111002_b0075","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1016\/S2213-2600(20)30168-5","article-title":"Interstitial lung abnormalities detected incidentally on CT: a position paper from the Fleischner Society","volume":"8","author":"Hatabu","year":"2020","journal-title":"Lancet Respir. Med."}],"container-title":["European Journal of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0720048X23003169?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0720048X23003169?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T07:38:20Z","timestamp":1759995500000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0720048X23003169"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":15,"alternative-id":["S0720048X23003169"],"URL":"https:\/\/doi.org\/10.1016\/j.ejrad.2023.111002","relation":{},"ISSN":["0720-048X"],"issn-type":[{"value":"0720-048X","type":"print"}],"subject":[],"published":{"date-parts":[[2023,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep learning-based automatic detection for pulmonary nodules on chest radiographs: The relationship with background lung condition, nodule characteristics, and location","name":"articletitle","label":"Article Title"},{"value":"European Journal of Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejrad.2023.111002","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"111002"}}