{"id":"https://openalex.org/W3095828274","doi":"https://doi.org/10.1109/tbdata.2020.3035935","title":"COVID-19-CT-CXR: A Freely Accessible and Weakly Labeled Chest X-Ray and CT Image Collection on COVID-19 From Biomedical Literature","display_name":"COVID-19-CT-CXR: A Freely Accessible and Weakly Labeled Chest X-Ray and CT Image Collection on COVID-19 From Biomedical Literature","publication_year":2020,"publication_date":"2020-11-04","ids":{"openalex":"https://openalex.org/W3095828274","doi":"https://doi.org/10.1109/tbdata.2020.3035935","mag":"3095828274","pmid":"https://pubmed.ncbi.nlm.nih.gov/32550254"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2020.3035935","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3035935","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tbdata.2020.3035935","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085113833","display_name":"Yifan Peng","orcid":"https://orcid.org/0000-0001-9309-8331"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4387153466","display_name":"Weill Cornell Medicine","ror":"https://ror.org/02r109517","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4387153466"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Peng","raw_affiliation_strings":["NCBI/NLM/NIH and Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065 USA","NCBI/NLM/NIH and Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0001-9309-8331","affiliations":[{"raw_affiliation_string":"NCBI/NLM/NIH and Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065 USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"NCBI/NLM/NIH and Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4387153466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037675893","display_name":"Yuxing Tang","orcid":"https://orcid.org/0000-0002-6452-2751"},"institutions":[{"id":"https://openalex.org/I4210155647","display_name":"National Institutes of Health Clinical Center","ror":"https://ror.org/04vfsmv21","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210155647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxing Tang","raw_affiliation_strings":["Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA","Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA","institution_ids":["https://openalex.org/I4210155647"]},{"raw_affiliation_string":"Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA","institution_ids":["https://openalex.org/I4210155647"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100713643","display_name":"Sungwon Lee","orcid":"https://orcid.org/0000-0002-1684-2996"},"institutions":[{"id":"https://openalex.org/I4210155647","display_name":"National Institutes of Health Clinical Center","ror":"https://ror.org/04vfsmv21","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210155647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sungwon Lee","raw_affiliation_strings":["Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA","Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-1684-2996","affiliations":[{"raw_affiliation_string":"Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA","institution_ids":["https://openalex.org/I4210155647"]},{"raw_affiliation_string":"Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA","institution_ids":["https://openalex.org/I4210155647"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101865110","display_name":"Yingying Zhu","orcid":"https://orcid.org/0000-0003-3920-5890"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]},{"id":"https://openalex.org/I4210155647","display_name":"National Institutes of Health Clinical Center","ror":"https://ror.org/04vfsmv21","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210155647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingying Zhu","raw_affiliation_strings":["Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA, and also with the Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019 USA","Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA","Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA, and also with the Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019 USA","institution_ids":["https://openalex.org/I4210155647"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]},{"raw_affiliation_string":"Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA","institution_ids":["https://openalex.org/I4210155647"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016047550","display_name":"Ronald M. Summers","orcid":"https://orcid.org/0000-0001-8081-7376"},"institutions":[{"id":"https://openalex.org/I4210155647","display_name":"National Institutes of Health Clinical Center","ror":"https://ror.org/04vfsmv21","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210155647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ronald M. Summers","raw_affiliation_strings":["Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA","Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA"],"raw_orcid":"https://orcid.org/0000-0001-8081-7376","affiliations":[{"raw_affiliation_string":"Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health (NIH) Clinical Center, Bethesda, MD 20892 USA","institution_ids":["https://openalex.org/I4210155647"]},{"raw_affiliation_string":"Radiology and Imaging Sciences Department, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA","institution_ids":["https://openalex.org/I4210155647"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083081872","display_name":"Zhiyong Lu","orcid":"https://orcid.org/0000-0001-9998-916X"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I4210109390","display_name":"National Center for Biotechnology Information","ror":"https://ror.org/02meqm098","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410","https://openalex.org/I4210109390"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiyong Lu","raw_affiliation_strings":["National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, MD 20894 USA","National Library of Medicine (NLM), National Center for Biotechnology Information (NCBI), National Institutes of Health (NIH), Bethesda, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, MD 20894 USA","institution_ids":["https://openalex.org/I4210109390"]},{"raw_affiliation_string":"National Library of Medicine (NLM), National Center for Biotechnology Information (NCBI), National Institutes of Health (NIH), Bethesda, MD, USA","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210109390"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2045,"currency":"USD","value_usd":2045},"apc_paid":{"value":2045,"currency":"USD","value_usd":2045},"fwci":7.2535,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":{"value":0.98012578,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"7","issue":"1","first_page":"3","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9581999778747559,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.8261624574661255},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5346307754516602},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5307835340499878},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5228008031845093},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.4548906981945038},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.44725140929222107},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.42173510789871216},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.39018964767456055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.358447790145874},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.34879398345947266},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.1298178732395172},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.08181700110435486}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.8261624574661255},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5346307754516602},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5307835340499878},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5228008031845093},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.4548906981945038},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.44725140929222107},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.42173510789871216},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.39018964767456055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.358447790145874},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.34879398345947266},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1298178732395172},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.08181700110435486},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tbdata.2020.3035935","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3035935","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},{"id":"pmid:32550254","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32550254","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ArXiv","raw_type":"Preprint"},{"id":"pmid:33997112","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33997112","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on big data","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:7298731","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7298731","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ArXiv","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8117951","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8117951","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Big Data","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/tbdata.2020.3035935","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3035935","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.44999998807907104,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1580422627","display_name":null,"funder_award_id":"4R00LM013001","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"},{"id":"https://openalex.org/G568654730","display_name":"A framework to enhance radiology structured report by invoking NLP and DL:  Models and Applications","funder_award_id":"5r00lm013001-03","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G691527071","display_name":null,"funder_award_id":"R00 LM013001","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"},{"id":"https://openalex.org/F4320337376","display_name":"NIH Clinical Center","ror":"https://ror.org/04vfsmv21"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1563795667","https://openalex.org/W1971303936","https://openalex.org/W2042014073","https://openalex.org/W2117123654","https://openalex.org/W2117539524","https://openalex.org/W2122646361","https://openalex.org/W2183341477","https://openalex.org/W2290195878","https://openalex.org/W2509752429","https://openalex.org/W2602628042","https://openalex.org/W2611650229","https://openalex.org/W2778310824","https://openalex.org/W2786189816","https://openalex.org/W2795424778","https://openalex.org/W2883683269","https://openalex.org/W2889630644","https://openalex.org/W2913279579","https://openalex.org/W2915895751","https://openalex.org/W2948269756","https://openalex.org/W2963243407","https://openalex.org/W2963373823","https://openalex.org/W2963446712","https://openalex.org/W2963466845","https://openalex.org/W2967094020","https://openalex.org/W2981020605","https://openalex.org/W2985737313","https://openalex.org/W2995225687","https://openalex.org/W3002108456","https://openalex.org/W3004824173","https://openalex.org/W3005079553","https://openalex.org/W3005879071","https://openalex.org/W3006110666","https://openalex.org/W3007170347","https://openalex.org/W3007273493","https://openalex.org/W3008827533","https://openalex.org/W3008928028","https://openalex.org/W3009926341","https://openalex.org/W3011414569","https://openalex.org/W3012857944","https://openalex.org/W3013515352","https://openalex.org/W3013564598","https://openalex.org/W3014337038","https://openalex.org/W3014725478","https://openalex.org/W3017243633","https://openalex.org/W3020653337","https://openalex.org/W3020786614","https://openalex.org/W3023827256","https://openalex.org/W3025404316","https://openalex.org/W3025948831","https://openalex.org/W3037538421","https://openalex.org/W3096956107","https://openalex.org/W3101156210","https://openalex.org/W3104049173","https://openalex.org/W3104810384","https://openalex.org/W3126632813","https://openalex.org/W3133191822","https://openalex.org/W3165656738","https://openalex.org/W4394659038","https://openalex.org/W6633802082","https://openalex.org/W6747741389","https://openalex.org/W6775691167","https://openalex.org/W6775859349","https://openalex.org/W6775884374","https://openalex.org/W6776225533","https://openalex.org/W6864221351"],"related_works":["https://openalex.org/W4206669628","https://openalex.org/W4224279380","https://openalex.org/W4205317059","https://openalex.org/W3176864053","https://openalex.org/W4206651655","https://openalex.org/W4206548596","https://openalex.org/W4292098121","https://openalex.org/W4210433452","https://openalex.org/W3036314732","https://openalex.org/W3084808338"],"abstract_inverted_index":{"The":[0,135,332],"latest":[1],"threat":[2],"to":[3,32,123,131,178,180,209,218,248,274,315,324],"global":[4],"health":[5],"is":[6,40,176,285,313],"the":[7,36,48,79,96,156,186,276,280,288,306,329],"COVID-19":[8,25,66,111,189,250,269,330],"outbreak.":[9],"Although":[10],"there":[11,39],"exist":[12],"large":[13,106],"datasets":[14],"of":[15,44,65,108,146,158,188,198,222,230,268,272,328],"chest":[16],"X-rays":[17],"(CXR)":[18],"and":[19,68,91,98,130,141,190,211,244,256,264,299,318,335],"computed":[20],"tomography":[21],"(CT)":[22],"scans,":[23],"few":[24],"image":[26,326],"collections":[27],"are":[28,72,113,290,338],"currently":[29],"available":[30,340],"due":[31],"patient":[33],"privacy.":[34],"At":[35],"same":[37],"time,":[38],"a":[41,62,105,120,213,220],"rapid":[42],"growth":[43],"COVID-19-relevant":[45,76],"articles":[46,77,112],"in":[47,95,110,279,305],"biomedical":[49],"literature,":[50],"including":[51],"those":[52,271],"that":[53,168,205,310,320],"report":[54],"findings":[55,267],"on":[56,232],"radiographs.":[57],"Here,":[58],"we":[59,118,160,259],"present":[60,207],"COVID-19-CT-CXR,":[61,159,169],"public":[63],"database":[64,137,284],"CXR":[67,115,143,243],"CT":[69,140,196],"images,":[70],"which":[71],"automatically":[73],"extracted":[74,87],"from":[75,78,126,241],"PubMed":[80],"Central":[81],"Open":[82],"Access":[83],"(PMC-OA)":[84],"Subset.":[85],"We":[86,166,194,235,308],"figures,":[88],"associated":[89],"captions,":[90],"relevant":[92,152,294],"figure":[93,128,257],"descriptions":[94],"article":[97],"separated":[99],"compound":[100],"figures":[101,109,289],"into":[102],"subfigures.":[103],"Because":[104],"portion":[107],"not":[114],"or":[116,225,227],"CT,":[117],"designed":[119],"deep-learning":[121,182],"model":[122],"distinguish":[124,219],"them":[125,133],"other":[127,228],"types":[129,229],"classify":[132],"accordingly.":[134],"final":[136],"includes":[138],"1,327":[139],"263":[142],"images":[144,197],"(as":[145],"May":[147],"9,":[148],"2020)":[149],"with":[150,293,296],"their":[151],"text.":[153],"To":[154],"demonstrate":[155,275],"utility":[157],"conducted":[161],"four":[162],"case":[163],"studies.":[164],"(1)":[165],"show":[167],"when":[170],"used":[171],"as":[172,287],"additional":[173],"training":[174],"data,":[175],"able":[177],"contribute":[179,323],"improved":[181],"(DL)":[183],"performance":[184],"for":[185],"classification":[187],"non-COVID-19":[191,242],"CT.":[192,233],"(2)":[193],"collected":[195],"influenza,":[199,224],"another":[200],"common":[201],"infectious":[202],"respiratory":[203],"illness":[204],"may":[206],"similarly":[208],"COVID-19,":[210,223],"fine-tuned":[212,236],"baseline":[214],"deep":[215],"neural":[216],"network":[217],"diagnosis":[221],"normal":[226],"diseases":[231],"(3)":[234],"an":[237],"unsupervised":[238],"one-class":[239],"classifier":[240],"performed":[245],"anomaly":[246],"detection":[247],"detect":[249],"CXR.":[251],"(4)":[252],"From":[253],"text-mined":[254],"captions":[255],"descriptions,":[258,298],"compared":[260],"15":[261],"clinical":[262,266],"symptoms":[263],"20":[265],"versus":[270],"influenza":[273],"disease":[277],"differences":[278],"scientific":[281],"publications.":[282],"Our":[283],"unique,":[286],"retrieved":[291],"along":[292],"text":[295],"fine-grained":[297],"it":[300,321],"can":[301],"be":[302],"extended":[303],"easily":[304],"future.":[307],"believe":[309],"our":[311],"work":[312],"complementary":[314],"existing":[316],"resources":[317],"hope":[319],"will":[322],"medical":[325],"analysis":[327],"pandemic.":[331],"dataset,":[333],"code,":[334],"DL":[336],"models":[337],"publicly":[339],"at":[341],"https://github.com/ncbi-nlp/COVID-19-CT-CXR.":[342]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":3}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2020-11-09T00:00:00"}