{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:20:52Z","timestamp":1750220452490,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,3,19]],"date-time":"2021-03-19T00:00:00Z","timestamp":1616112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,3,19]]},"DOI":"10.1145\/3460569.3460591","type":"proceedings-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T16:24:32Z","timestamp":1630427072000},"page":"51-58","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["COVID-19 detection by X-Ray images and Deep Learning"],"prefix":"10.1145","author":[{"given":"Namrig.","family":"H.S. FEDAL","sequence":"first","affiliation":[{"name":"university of Gazi, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahir","family":"DURSUN","sequence":"additional","affiliation":[{"name":"university of Gazi, turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"1","article-title":"Covid-19: automatic detection from x-ray images utilizing transfer learning with convolutional neural networks","author":"Apostolopoulos T. A.","year":"2020","journal-title":"Physical and Engineering Sciences in Medicine"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2989273"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1101\/2020.03.12.20027185"},{"volume-title":"Covid-resnet: A deep learning framework for screening of covid19 from radiographs","year":"2003","author":"Farooq A.","key":"e_1_3_2_1_4_1"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/3026877.3026899"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.01.082"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Kong W Agarwal PP. Chest imaging appearance of COVID-19 infection. Radiology: Cardiothoracic Imaging. (2020) 2: e200028. doi: 10.1148\/ryct.2020200028  Kong W Agarwal PP. Chest imaging appearance of COVID-19 infection. Radiology: Cardiothoracic Imaging. (2020) 2:e200028. doi: 10.1148\/ryct.2020200028","DOI":"10.1148\/ryct.2020200028"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Hansell DM Bankier AA MacMahon H McLoud TC Muller NL Remy J. Fleischner society: glossary of terms for thoracic imaging. Radiology. (2008) 246: 697\u2013722. doi: 10.1148\/radiol.2462070712  Hansell DM Bankier AA MacMahon H McLoud TC Muller NL Remy J. Fleischner society: glossary of terms for thoracic imaging. Radiology. (2008) 246:697\u2013722. doi: 10.1148\/radiol.2462070712","DOI":"10.1148\/radiol.2462070712"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Rodrigues J Hare S Edey A Devaraj A Jacob J Johnstone A An update on COVID-19 for the radiologist-A British society of Thoracic Imaging statement. Clin Radiol. (2020) 75: 323\u20135. doi: 10.1016\/j.crad.2020.03.003.  Rodrigues J Hare S Edey A Devaraj A Jacob J Johnstone A An update on COVID-19 for the radiologist-A British society of Thoracic Imaging statement. Clin Radiol. (2020) 75:323\u20135. doi: 10.1016\/j.crad.2020.03.003.","DOI":"10.1016\/j.crad.2020.03.003"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Chung M Bernheim A Mei X Zhang N Huang M Zeng X CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology. (2020) 295: 202\u20137. doi: 10.1148\/radiol.2020200230 .  Chung M Bernheim A Mei X Zhang N Huang M Zeng X CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology. (2020) 295:202\u20137. doi: 10.1148\/radiol.2020200230 .","DOI":"10.1148\/radiol.2020200230"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Asif Sohaib \"Classification of covid-19 from chest x-ray images using deep convolutional neural networks.\"\u00a0 medRxiv\u00a0(2020).  Asif Sohaib \"Classification of covid-19 from chest x-ray images using deep convolutional neural networks.\"\u00a0 medRxiv\u00a0(2020).","DOI":"10.1109\/ICCC51575.2020.9344870"},{"key":"e_1_3_2_1_12_1","first-page":"97","article-title":"Detection and differentiation of COVID-19 using deep learning approach fed by x-rays","volume":"3","author":"Erda\u015f","year":"2020","journal-title":"\u00a0 International Journal of Applied Mathematics Electronics and Computers\u00a08"},{"volume-title":"Coronet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images.\u00a0 Computer Methods and Programs in Biomedicine, 105581","year":"2020","author":"Khan A. I.","key":"e_1_3_2_1_13_1"},{"volume-title":"Covid-net: A tailored deep convolutional neural network design for detection of covid-19 cases from chest x-ray images.\u00a0 Scientific Reports,\u00a010 (1), 1-12","year":"2020","author":"Wang L.","key":"e_1_3_2_1_14_1"},{"key":"e_1_3_2_1_15_1","unstructured":"F. Shiet al. \u201cLarge-scale screening of covid-19 from communityacquired pneumonia using infection size-aware classification \u201darXivpreprint arXiv:2003.09860 2020.  F. Shiet al. \u201cLarge-scale screening of covid-19 from communityacquired pneumonia using infection size-aware classification \u201darXivpreprint arXiv:2003.09860 2020."},{"volume-title":"Covid-19: automatic detection from x-ray images utilizing transfer learning with convolutional neural networks. Physical and Engineering Sciences in Medicine, 1.\u00a0","year":"2020","author":"Apostolopoulos I. D.","key":"e_1_3_2_1_16_1"},{"volume-title":"Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networks. arXiv preprint arXiv:2003.10849","year":"2020","author":"Narin A.","key":"e_1_3_2_1_17_1"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.20944\/preprints202003.0300.v1"}],"event":{"name":"ICMAI 2021: 2021 6th International Conference on Mathematics and Artificial Intelligence","acronym":"ICMAI 2021","location":"Chengdu China"},"container-title":["2021 6th International Conference on Mathematics and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460569.3460591","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3460569.3460591","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:56Z","timestamp":1750193276000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460569.3460591"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,19]]},"references-count":18,"alternative-id":["10.1145\/3460569.3460591","10.1145\/3460569"],"URL":"https:\/\/doi.org\/10.1145\/3460569.3460591","relation":{},"subject":[],"published":{"date-parts":[[2021,3,19]]},"assertion":[{"value":"2021-08-31","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}