{"id":"https://openalex.org/W3198214205","doi":"https://doi.org/10.1145/3460569.3460591","title":"COVID-19 detection by X-Ray images and Deep Learning","display_name":"COVID-19 detection by X-Ray images and Deep Learning","publication_year":2021,"publication_date":"2021-03-19","ids":{"openalex":"https://openalex.org/W3198214205","doi":"https://doi.org/10.1145/3460569.3460591","mag":"3198214205"},"language":"en","primary_location":{"id":"doi:10.1145/3460569.3460591","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460569.3460591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th International Conference on Mathematics and Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018859914","display_name":"Namrig. H.S. FEDAL","orcid":null},"institutions":[{"id":"https://openalex.org/I95634034","display_name":"Gazi University","ror":"https://ror.org/054xkpr46","country_code":"TR","type":"education","lineage":["https://openalex.org/I95634034"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Namrig. H.S. FEDAL","raw_affiliation_strings":["university of Gazi, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"university of Gazi, Turkey","institution_ids":["https://openalex.org/I95634034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017001574","display_name":"Mahir Dursun","orcid":"https://orcid.org/0000-0003-0649-2627"},"institutions":[{"id":"https://openalex.org/I95634034","display_name":"Gazi University","ror":"https://ror.org/054xkpr46","country_code":"TR","type":"education","lineage":["https://openalex.org/I95634034"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Mahir DURSUN","raw_affiliation_strings":["university of Gazi, turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"university of Gazi, turkey","institution_ids":["https://openalex.org/I95634034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I95634034"],"apc_list":null,"apc_paid":null,"fwci":0.5961,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63417358,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"51","last_page":"58"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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":1.0,"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":0.9866999983787537,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9811999797821045,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.8243727684020996},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7885140180587769},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.7567339539527893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7158218622207642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6618441343307495},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.6462001204490662},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4878411293029785},{"id":"https://openalex.org/keywords/radiography","display_name":"Radiography","score":0.4610990285873413},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44190889596939087},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.4342171549797058},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4088556468486786},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35567042231559753},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.33752015233039856},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.29001909494400024},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.23377197980880737},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.19990602135658264},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.10672876238822937}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.8243727684020996},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7885140180587769},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.7567339539527893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7158218622207642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6618441343307495},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.6462001204490662},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4878411293029785},{"id":"https://openalex.org/C36454342","wikidata":"https://www.wikidata.org/wiki/Q245341","display_name":"Radiography","level":2,"score":0.4610990285873413},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44190889596939087},{"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":0.4342171549797058},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4088556468486786},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35567042231559753},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.33752015233039856},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.29001909494400024},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.23377197980880737},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.19990602135658264},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.10672876238822937}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3460569.3460591","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460569.3460591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th International Conference on Mathematics and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2102634410","https://openalex.org/W2289846183","https://openalex.org/W2402144811","https://openalex.org/W3004906315","https://openalex.org/W3006627382","https://openalex.org/W3010702679","https://openalex.org/W3011414569","https://openalex.org/W3012843799","https://openalex.org/W3013601031","https://openalex.org/W3014322576","https://openalex.org/W3019899894","https://openalex.org/W3022719712","https://openalex.org/W3091599926","https://openalex.org/W3132499588"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W2964954556","https://openalex.org/W3029198973"],"abstract_inverted_index":{"The":[0,16,41,118],"new":[1],"Coronavirus,":[2],"also":[3,158],"called":[4],"COVID-19,":[5],"appeared":[6],"in":[7,10,64,72,88,98,177],"Wuhan,":[8],"China":[9],"December":[11],"2019":[12],"Spread":[13],"out":[14],"big.":[15],"virus":[17,28],"has":[18,29,142],"now":[19],"made":[20],"the":[21,31,36,53,65,73,126,146,163,166,171,178,191],"COVID-19":[22,45,70],"disease":[23,71],"a":[24,47,135,209],"worldwide":[25],"epidemic.":[26],"This":[27,156],"affected":[30],"global":[32],"health,":[33],"economy,":[34],"and":[35,67,201,214],"daily":[37],"lives":[38],"of":[39,44,55,69,121,128,148,165,181,212,217],"individuals.":[40],"timely":[42],"diagnosis":[43,68,180],"is":[46,125],"crucial":[48],"task":[49],"as":[50,81,92],"it":[51],"reduces":[52],"risk":[54],"pandemic":[56],"spread.":[57],"Chest":[58],"x-rays":[59],"play":[60],"an":[61],"important":[62],"role":[63],"testing":[66],"recent":[74],"pandemic.":[75],"Advanced":[76],"Artificial":[77],"Intelligence":[78],"techniques":[79],"such":[80,91],"Deep":[82],"Learning":[83],"have":[84],"shown":[85],"high":[86],"efficiency":[87],"detecting":[89],"patterns":[90],"those":[93],"that":[94],"can":[95],"be":[96],"found":[97],"diseased":[99],"tissue,":[100],"so":[101],"convolution":[102],"neural":[103],"networks":[104],"were":[105],"evaluated":[106],"for":[107,145],"their":[108,175],"ability":[109],"to":[110,161],"detect":[111],"infected":[112,150],"patients":[113,151],"from":[114,183],"chest":[115,153],"X-ray":[116,154],"images.":[117,205],"key":[119],"component":[120],"deep":[122],"learning":[123],"research":[124],"availability":[127],"training":[129],"data":[130],"sets.":[131],"In":[132],"this":[133],"study,":[134],"parallel":[136],"Convolutional":[137],"Neural":[138],"Networks":[139],"(CNNs)":[140],"model":[141,193],"been":[143],"proposed":[144,169],"detection":[147],"covid-19":[149],"using":[152,196],"radiographs.":[155],"paper":[157],"presents":[159],"how":[160],"evaluate":[162],"effectiveness":[164],"state-of-the-art":[167],"CNN":[168,192],"by":[170,195],"scientific":[172],"community":[173],"about":[174],"expertise":[176],"automatic":[179],"Covid-19":[182,198,203],"thoracic":[184],"x-rays.":[185],"To":[186],"validate":[187],"results,":[188],"we":[189],"trained":[190],"network":[194],"500":[197],"Positive":[199],"images":[200],"1600":[202],"Negative":[204],"It":[206],"was":[207],"given":[208],"classification":[210],"accuracy":[211,216],"90%":[213],"validation":[215],"88%.":[218]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}