{"id":"https://openalex.org/W4312386400","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936837","title":"Identification of COVID-19 from Chest CT Scan Using CNN as Feature Extractor and Voting Classifier","display_name":"Identification of COVID-19 from Chest CT Scan Using CNN as Feature Extractor and Voting Classifier","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4312386400","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936837"},"language":"en","primary_location":{"id":"doi:10.1109/iicaiet55139.2022.9936837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936837","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","raw_type":"proceedings-article"},"type":"article","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/A5033947546","display_name":"Ferdib-Al Islam","orcid":null},"institutions":[{"id":"https://openalex.org/I1307585291","display_name":"Khulna University of Engineering and Technology","ror":"https://ror.org/04y58d606","country_code":"BD","type":"education","lineage":["https://openalex.org/I1307585291"]}],"countries":["BD"],"is_corresponding":true,"raw_author_name":"Ferdib-Al-Islam","raw_affiliation_strings":["Khulna University of Engineering & Technology,Department of Computer Science and Engineering,Khulna,Bangladesh"],"affiliations":[{"raw_affiliation_string":"Khulna University of Engineering & Technology,Department of Computer Science and Engineering,Khulna,Bangladesh","institution_ids":["https://openalex.org/I1307585291"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066829510","display_name":"Pintu Chandra Shill","orcid":"https://orcid.org/0000-0002-6395-9281"},"institutions":[{"id":"https://openalex.org/I1307585291","display_name":"Khulna University of Engineering and Technology","ror":"https://ror.org/04y58d606","country_code":"BD","type":"education","lineage":["https://openalex.org/I1307585291"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Pintu Chandra Shill","raw_affiliation_strings":["Khulna University of Engineering & Technology,Department of Computer Science and Engineering,Khulna,Bangladesh"],"affiliations":[{"raw_affiliation_string":"Khulna University of Engineering & Technology,Department of Computer Science and Engineering,Khulna,Bangladesh","institution_ids":["https://openalex.org/I1307585291"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033947546"],"corresponding_institution_ids":["https://openalex.org/I1307585291"],"apc_list":null,"apc_paid":null,"fwci":1.5621,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8805568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9643999934196472,"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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9535999894142151,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6957415342330933},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6400946974754333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6198043823242188},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.5812341570854187},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5738546848297119},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5495764017105103},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5364810228347778},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49386006593704224},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.43556809425354004},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4154094457626343},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39012932777404785},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3441510796546936},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.27477917075157166},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.23104768991470337},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.1377081274986267},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1257091760635376},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.1248960793018341}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6957415342330933},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6400946974754333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6198043823242188},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.5812341570854187},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5738546848297119},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5495764017105103},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5364810228347778},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49386006593704224},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.43556809425354004},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4154094457626343},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39012932777404785},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3441510796546936},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27477917075157166},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.23104768991470337},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.1377081274986267},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1257091760635376},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.1248960793018341}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iicaiet55139.2022.9936837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936837","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W3007764760","https://openalex.org/W3011739897","https://openalex.org/W3013004778","https://openalex.org/W3013507463","https://openalex.org/W3014725478","https://openalex.org/W3015292413","https://openalex.org/W3017855299","https://openalex.org/W3021476631","https://openalex.org/W3022592783","https://openalex.org/W3026637813","https://openalex.org/W3033616466","https://openalex.org/W3034560014","https://openalex.org/W3045460727","https://openalex.org/W3082003320","https://openalex.org/W3083161015","https://openalex.org/W3083753334","https://openalex.org/W3088947319","https://openalex.org/W3091978650","https://openalex.org/W3104810384","https://openalex.org/W3104951425","https://openalex.org/W3200595640","https://openalex.org/W6777714645"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W2965782936","https://openalex.org/W4323287533","https://openalex.org/W4360994352"],"abstract_inverted_index":{"COVID-19":[0,46,70,113],"was":[1,131,137,152],"first":[2],"identified":[3],"in":[4,14,78,85],"Wuhan":[5],"(China)":[6],"and":[7,30,53,92,133,170,186],"swiftly":[8],"spread":[9],"over":[10],"the":[11,69,86,96,109,160],"world,":[12],"resulting":[13],"a":[15,22,106,127],"global":[16],"pandemic":[17],"emergency.":[18],"It":[19],"has":[20],"had":[21],"profound":[23],"effect":[24],"on":[25],"everyday":[26],"living,":[27],"general":[28],"well-being,":[29],"international":[31],"finance.":[32],"Rapid":[33],"diagnosis":[34],"of":[35,68,74,89,98,112,148,178,184,188],"susceptible":[36],"people":[37],"is":[38,41,51],"critical.":[39],"There":[40],"no":[42],"precise":[43],"testing":[44],"for":[45,48,108],"except":[47],"RT-PCR,":[49],"which":[50],"expensive":[52],"time-consuming.":[54],"Recent":[55],"studies":[56],"conducted":[57],"using":[58,115],"radiological":[59],"imaging":[60,82],"techniques":[61],"suggest":[62],"that":[63],"such":[64],"pictures":[65],"include":[66],"characteristics":[67],"infection.":[71],"The":[72,143,172],"implication":[73],"machine":[75,149],"learning":[76,150],"algorithms":[77],"conjunction":[79],"with":[80],"chest":[81,116,124],"may":[83],"aid":[84],"accurate":[87,156],"detection":[88],"this":[90],"illness":[91],"help":[93],"to":[94,104,139,154],"overcome":[95],"shortage":[97],"specialized":[99],"physicians.":[100],"This":[101],"work":[102],"aims":[103],"construct":[105],"model":[107,145,174],"automated":[110],"recognition":[111],"infection":[114],"CT":[117,125],"scans.":[118],"To":[119],"extract":[120],"features":[121],"from":[122],"patient's":[123],"scans,":[126],"convolutional":[128],"neural":[129],"network":[130],"used,":[132],"Principle":[134],"Component":[135],"Analysis":[136],"used":[138],"decrease":[140],"computing":[141],"cost.":[142],"proposed":[144,173],"(an":[146],"ensemble":[147],"classifiers)":[151],"created":[153],"offer":[155],"diagnostics":[157],"by":[158],"incorporating":[159],"five":[161],"categories":[162],"(Normal,":[163],"Mycoplasma":[164],"pneumonia,":[165,167,169],"Bacterial":[166],"Viral":[168],"COVID-19).":[171],"reached":[175],"an":[176],"accuracy":[177],"99.3%,":[179,185],"positive":[180],"predictive":[181],"value":[182],"(ppv)":[183],"sensitivity":[187],"99.2":[189],"%.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2023-01-04T00:00:00"}