{"id":"https://openalex.org/W2896426296","doi":"https://doi.org/10.1109/access.2018.2875406","title":"DeepCXray: Automatically Diagnosing Diseases on Chest X-Rays Using Deep Neural Networks","display_name":"DeepCXray: Automatically Diagnosing Diseases on Chest X-Rays Using Deep Neural Networks","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2896426296","doi":"https://doi.org/10.1109/access.2018.2875406","mag":"2896426296"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2875406","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875406","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2875406","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100548425","display_name":"Xiuyuan Xu","orcid":"https://orcid.org/0009-0006-4526-2946"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiuyuan Xu","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112307326","display_name":"Quan Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Guo","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091066995","display_name":"Jixiang Guo","orcid":"https://orcid.org/0000-0002-1678-8205"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jixiang Guo","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100388188","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-5867-9322"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Yi","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-5867-9322","affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100548425"],"corresponding_institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2948,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.81389198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"66972","last_page":"66983"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7643677592277527},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7557789087295532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7095234990119934},{"id":"https://openalex.org/keywords/economic-shortage","display_name":"Economic shortage","score":0.6755894422531128},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5967535376548767},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5829662084579468},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5629244446754456},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5519037246704102},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.509252667427063},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4319901466369629},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3694817125797272},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30889952182769775}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7643677592277527},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7557789087295532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7095234990119934},{"id":"https://openalex.org/C194051981","wikidata":"https://www.wikidata.org/wiki/Q1337691","display_name":"Economic shortage","level":3,"score":0.6755894422531128},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5967535376548767},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5829662084579468},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5629244446754456},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5519037246704102},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.509252667427063},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4319901466369629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3694817125797272},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30889952182769775},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2875406","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875406","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c7238a45a9db4bb5a1ccfb7420455886","is_oa":true,"landing_page_url":"https://doaj.org/article/c7238a45a9db4bb5a1ccfb7420455886","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 66972-66983 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2875406","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875406","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G7411043749","display_name":null,"funder_award_id":"U1435213","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7670333304","display_name":null,"funder_award_id":"61432012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W75432400","https://openalex.org/W197865394","https://openalex.org/W1503432700","https://openalex.org/W1686810756","https://openalex.org/W1799366690","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W1884191083","https://openalex.org/W1905153633","https://openalex.org/W1971361999","https://openalex.org/W1974823213","https://openalex.org/W1980501707","https://openalex.org/W2010382953","https://openalex.org/W2077554240","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2119191234","https://openalex.org/W2133533561","https://openalex.org/W2136922672","https://openalex.org/W2139393465","https://openalex.org/W2163605009","https://openalex.org/W2164122462","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2336559488","https://openalex.org/W2504150216","https://openalex.org/W2511730936","https://openalex.org/W2520774990","https://openalex.org/W2557738935","https://openalex.org/W2562319768","https://openalex.org/W2581082771","https://openalex.org/W2611650229","https://openalex.org/W2765312638","https://openalex.org/W2767106145","https://openalex.org/W2770241596","https://openalex.org/W2913340405","https://openalex.org/W2949117887","https://openalex.org/W2949650786","https://openalex.org/W2963446712","https://openalex.org/W2963673193","https://openalex.org/W2964350391","https://openalex.org/W3101156210","https://openalex.org/W4232097126","https://openalex.org/W4234643200","https://openalex.org/W4295608163","https://openalex.org/W4300485340","https://openalex.org/W6603049871","https://openalex.org/W6639204139","https://openalex.org/W6680919041","https://openalex.org/W6684191040","https://openalex.org/W6694260854","https://openalex.org/W6726946684"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2761785940","https://openalex.org/W2129933262"],"abstract_inverted_index":{"The":[0,88,157],"automatic":[1],"detection":[2],"of":[3,18,21,46,59,76,81,92,110,153,175,192,196,215,221,225,229],"diseases":[4],"in":[5,14,48,70,227],"images":[6,97,105],"acquired":[7,29],"through":[8,30],"chest":[9,31,95],"X-rays":[10,32],"can":[11,187],"be":[12],"useful":[13],"clinical":[15],"diagnosis":[16,93],"because":[17,80],"a":[19,60,71,119,143,162,206],"shortage":[20],"experienced":[22],"doctors.":[23],"Compared":[24],"with":[25],"natural":[26],"images,":[27,141],"those":[28],"are":[33,43,69,86,98],"obtained":[34,84],"by":[35,199,205],"using":[36],"penetrating":[37],"imaging":[38],"technology,":[39],"such":[40],"that":[41,125,170],"there":[42],"multiple":[44],"levels":[45],"features":[47,58,102,138],"an":[49,193],"image.":[50],"It":[51],"is":[52,134,147,161],"thus":[53],"difficult":[54],"to":[55,99,136,149,177],"extract":[56,100,137],"the":[57,74,83,108,151,173,183,190,212,218,222,230,233],"disease":[61,78],"for":[62],"further":[63],"diagnosis.":[64],"In":[65,114,180],"practice,":[66],"healthy":[67],"people":[68],"majority":[72],"and":[73,106,142],"morbidities":[75],"different":[77,207],"vary,":[79],"which":[82],"labels":[85],"imbalanced.":[87],"two":[89,129],"main":[90],"challenges":[91],"though":[94],"X-ray":[96,104],"discriminative":[101],"from":[103,139],"handle":[107],"problem":[109,152],"imbalanced":[111,154],"data":[112,155],"distribution.":[113,156],"this":[115],"paper,":[116],"we":[117],"propose":[118],"deep":[120],"neural":[121],"network":[122],"called":[123],"DeepCXray":[124,216],"simultaneously":[126],"solves":[127],"these":[128],"problems.":[130],"An":[131],"InceptionV3":[132],"model":[133],"trained":[135],"raw":[140],"new":[144],"objective":[145,159],"function":[146,160,186],"designed":[148],"address":[150],"proposed":[158,184],"performance":[163,214],"index":[164],"based":[165],"on":[166,217],"cross":[167,202],"entropy":[168,203],"loss":[169,185],"automatically":[171,188],"weights":[172],"ratio":[174],"positive":[176],"negative":[178,197],"samples.":[179],"other":[181],"words,":[182],"reduce":[189],"influence":[191],"overwhelming":[194],"number":[195],"samples":[198],"shrinking":[200],"each":[201],"terms":[204,228],"extent.":[208],"Extensive":[209],"experiments":[210],"highlight":[211],"promising":[213],"ChestXray14":[219],"dataset":[220],"National":[223],"Institutes":[224],"Health":[226],"area":[231],"under":[232],"receiver":[234],"operating":[235],"characteristic":[236],"curve.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
