{"id":"https://openalex.org/W4385488997","doi":"https://doi.org/10.1109/icasspw59220.2023.10193422","title":"AI-Enabled Analysis of 3-D CT Scans for Diagnosis of COVID-19 & its Severity","display_name":"AI-Enabled Analysis of 3-D CT Scans for Diagnosis of COVID-19 & its Severity","publication_year":2023,"publication_date":"2023-06-04","ids":{"openalex":"https://openalex.org/W4385488997","doi":"https://doi.org/10.1109/icasspw59220.2023.10193422"},"language":"en","primary_location":{"id":"doi:10.1109/icasspw59220.2023.10193422","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icasspw59220.2023.10193422","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","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/A5029879679","display_name":"Dimitrios Kollias","orcid":"https://orcid.org/0000-0002-8188-3751"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dimitrios Kollias","raw_affiliation_strings":["Queen Mary University of London,UK","Queen Mary University of London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen Mary University of London,UK","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"Queen Mary University of London, UK","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016292531","display_name":"\u0391\u03bd\u03b1\u03c3\u03c4\u03ac\u03c3\u03b9\u03bf\u03c2 \u0391\u03c1\u03c3\u03ad\u03bd\u03bf\u03c2","orcid":"https://orcid.org/0009-0000-0332-6194"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Anastasios Arsenos","raw_affiliation_strings":["National Technical University of Athens,Greece","National Technical University of Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":"National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001457450","display_name":"Stefanos Kollias","orcid":"https://orcid.org/0000-0003-2899-0598"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stefanos Kollias","raw_affiliation_strings":["National Technical University of Athens,Greece","National Technical University of Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":"National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.1924,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.97967779,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T10862","display_name":"AI in cancer detection","score":0.9954000115394592,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9940999746322632,"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/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.831976056098938},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7412376403808594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6121980547904968},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5807408094406128},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.5107400417327881},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.49974632263183594},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.4935041666030884},{"id":"https://openalex.org/keywords/2019-20-coronavirus-outbreak","display_name":"2019-20 coronavirus outbreak","score":0.4743862450122833},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45631158351898193},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39542528986930847},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3394124507904053},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2588917315006256},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.2537253499031067},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.10993003845214844}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.831976056098938},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7412376403808594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6121980547904968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5807408094406128},{"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":0.5107400417327881},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.49974632263183594},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.4935041666030884},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.4743862450122833},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45631158351898193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39542528986930847},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3394124507904053},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2588917315006256},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2537253499031067},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.10993003845214844},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C116675565","wikidata":"https://www.wikidata.org/wiki/Q3241045","display_name":"Outbreak","level":2,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icasspw59220.2023.10193422","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icasspw59220.2023.10193422","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2769215776","https://openalex.org/W2979217664","https://openalex.org/W3021883287","https://openalex.org/W3086650124","https://openalex.org/W3121891683","https://openalex.org/W3154692872","https://openalex.org/W3208040116","https://openalex.org/W4283781721","https://openalex.org/W4283783828","https://openalex.org/W4283826401","https://openalex.org/W4283828318","https://openalex.org/W4283833825","https://openalex.org/W4285027808","https://openalex.org/W4288056207","https://openalex.org/W4320036953","https://openalex.org/W4320040760","https://openalex.org/W4320041095","https://openalex.org/W4367057073","https://openalex.org/W6782312386","https://openalex.org/W6839247522","https://openalex.org/W6839263110","https://openalex.org/W6839337992","https://openalex.org/W6839363558","https://openalex.org/W6840076149","https://openalex.org/W6840618553"],"related_works":["https://openalex.org/W4200329650","https://openalex.org/W3127156785","https://openalex.org/W4205754011","https://openalex.org/W3009669391","https://openalex.org/W4205215807","https://openalex.org/W3005417802","https://openalex.org/W4226296940","https://openalex.org/W3028835529","https://openalex.org/W3036314732","https://openalex.org/W3134376730"],"abstract_inverted_index":{"This":[0],"paper":[1,181],"describes":[2,183],"the":[3,10,18,39,53,68,99,103,109,122,141,184,188,205,208],"3rd":[4,32,76,189],"COVID-19":[5,33,77,128,150,190,211],"Competition,":[6,191],"taking":[7],"place":[8],"in":[9,67,102,158],"AI-enabled":[11],"medical":[12],"image":[13,58],"analysis":[14],"(AIMIA)":[15],"Workshop":[16],"of":[17,38,55,70,80,98,121,132,140,171,210],"2023":[19],"IEEE":[20],"International":[21],"Conference":[22],"on":[23,94,198,203],"Acoustics,":[24],"Speech":[25],"and":[26,45,49,59,62,73,86,105,130,161,169,207],"Signal":[27],"Processing":[28],"(ICASSP":[29],"2023).":[30],"The":[31,75,180],"Competition":[34,78],"is":[35,125,212],"a":[36],"continuation":[37],"Competitions":[40],"held":[41],"at":[42],"ECCV":[43],"2022":[44],"ICCV":[46],"2021":[47],"Conferences,":[48],"aims":[50],"to":[51,63,148],"tackle":[52],"challenges":[54],"whole":[56],"slide":[57],"CT/MRI/X-ray":[60],"analysis/processing":[61],"identify":[64],"research":[65],"opportunities":[66],"context":[69],"Digital":[71],"Pathology":[72],"Radiology/COVID19.":[74],"consists":[79,131],"two":[81],"Challenges":[82,91],"targeting":[83],"COVID19":[84,87],"detection":[85,129],"severity":[88,151,209],"detection.":[89],"Both":[90,153],"are":[92,143,165,193],"based":[93,197],"an":[95],"extended":[96],"version":[97],"database":[100,124,142],"used":[101,166],"1st":[104],"2nd":[106],"COV19D":[107],"Competitions,":[108],"COV19-CT-DB":[110,123],"database,":[111],"which":[112,192],"includes":[113],"chest":[114],"CT":[115,134,138],"scan":[116],"series.":[117],"A":[118],"large":[119],"part":[120],"annotated":[126,145],"for":[127,167,178,187],"8,0003-D":[133],"scans.":[135],"About":[136],"1,0003-D":[137],"scans":[139],"also":[144],"with":[146],"respect":[147],"four":[149],"conditions.":[152],"parts":[154],"have":[155],"been":[156],"split":[157],"training,":[159],"validation":[160,170],"test":[162],"datasets.":[163],"These":[164],"training":[168],"machine":[172],"learning":[173,195],"models,":[174],"as":[175,177],"well":[176],"evaluation.":[179],"further":[182],"baseline":[185],"methods":[186],"deep":[194],"approaches,":[196],"CNN-RNN":[199],"networks.":[200],"Their":[201],"performance":[202],"detecting":[204],"existence":[206],"reported.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}