{"id":"https://openalex.org/W4417250504","doi":"https://doi.org/10.1109/bibe66822.2025.00045","title":"Fairness-Aware Deep Learning Model for Covid19 Detection from Cough Audio Recordings","display_name":"Fairness-Aware Deep Learning Model for Covid19 Detection from Cough Audio Recordings","publication_year":2025,"publication_date":"2025-11-06","ids":{"openalex":"https://openalex.org/W4417250504","doi":"https://doi.org/10.1109/bibe66822.2025.00045"},"language":null,"primary_location":{"id":"doi:10.1109/bibe66822.2025.00045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe66822.2025.00045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Conference on Bioinformatics and Bioengineering (BIBE)","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/A5120775965","display_name":"Dimitra Kostavasili","orcid":null},"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":true,"raw_author_name":"Dimitra Kostavasili","raw_affiliation_strings":["School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021038994","display_name":"Theofanis Ganitidis","orcid":"https://orcid.org/0009-0006-7794-9793"},"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":"Theofanis Ganitidis","raw_affiliation_strings":["School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016849904","display_name":"\u039c\u03b1\u03c1\u03af\u03b1 \u0391\u03b8\u03b1\u03bd\u03b1\u03c3\u03af\u03bf\u03c5","orcid":"https://orcid.org/0000-0003-1575-9100"},"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":"Maria Athanasiou","raw_affiliation_strings":["School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082313849","display_name":"Konstantina S. Nikita","orcid":"https://orcid.org/0000-0001-8255-4354"},"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":"Konstantina S. Nikita","raw_affiliation_strings":["School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5120775965"],"corresponding_institution_ids":["https://openalex.org/I174458059"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56591347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"219","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8435999751091003,"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":0.8435999751091003,"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":0.03579999879002571,"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/T11448","display_name":"Face recognition and analysis","score":0.01510000042617321,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/deep-learning","display_name":"Deep learning","score":0.6937999725341797},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5877000093460083},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5659000277519226},{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.5123000144958496},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.4632999897003174},{"id":"https://openalex.org/keywords/odds","display_name":"Odds","score":0.46059998869895935},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4523000121116638},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4083000123500824},{"id":"https://openalex.org/keywords/learning-curve","display_name":"Learning curve","score":0.398499995470047}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7231000065803528},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6937999725341797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6549000144004822},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6079999804496765},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5877000093460083},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5659000277519226},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.5123000144958496},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.4632999897003174},{"id":"https://openalex.org/C143095724","wikidata":"https://www.wikidata.org/wiki/Q515895","display_name":"Odds","level":3,"score":0.46059998869895935},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4083000123500824},{"id":"https://openalex.org/C34585555","wikidata":"https://www.wikidata.org/wiki/Q1368723","display_name":"Learning curve","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.3928000032901764},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.34310001134872437},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.3393999934196472},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.33629998564720154},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C3020225094","wikidata":"https://www.wikidata.org/wiki/Q80091","display_name":"Area under curve","level":3,"score":0.29760000109672546},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2678999900817871},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.26159998774528503},{"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":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibe66822.2025.00045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe66822.2025.00045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Conference on Bioinformatics and Bioengineering (BIBE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2526050071","https://openalex.org/W2765995311","https://openalex.org/W3049658928","https://openalex.org/W3088067841","https://openalex.org/W3162810948","https://openalex.org/W3175510762","https://openalex.org/W3189722576","https://openalex.org/W4381685494","https://openalex.org/W4387435251","https://openalex.org/W4388421615","https://openalex.org/W4390607559","https://openalex.org/W4403510073","https://openalex.org/W4403811030","https://openalex.org/W4405271002","https://openalex.org/W4408302413","https://openalex.org/W4416961750"],"related_works":[],"abstract_inverted_index":{"The":[0,129],"COVID-19":[1,23,43,50],"pandemic":[2],"intensified":[3],"the":[4,49,110,154,160,168,178],"demand":[5],"for":[6,21,42,153],"rapid,":[7],"accessible":[8],"diagnostic":[9,175],"methods.":[10],"Machine":[11],"learning":[12,40,186],"models":[13,41],"using":[14,45],"cough":[15],"audio":[16],"recordings":[17],"have":[18],"shown":[19],"potential":[20],"remote":[22],"detection":[24],"but":[25],"often":[26],"exhibit":[27],"performance":[28],"disparities":[29],"across":[30,99],"demographic":[31],"and":[32,56,73,85,91,109,114,139,146,158,172],"clinical":[33,184],"subgroups.":[34],"This":[35],"study":[36],"investigates":[37],"fairness-aware":[38],"machine":[39,185],"diagnosis":[44],"crowdsourced":[46],"data":[47],"from":[48],"Sounds":[51],"dataset.":[52],"A":[53],"Random":[54],"Forest":[55],"a":[57,80,95],"VGGish-based":[58],"deep":[59],"neural":[60],"network":[61],"classifier":[62],"were":[63,71,135],"developed.":[64],"To":[65],"mitigate":[66],"bias,":[67],"four":[68],"different":[69],"methods":[70],"applied":[72],"comparatively":[74],"evaluated,":[75],"namely":[76],"correlation":[77],"remover":[78],"as":[79,88,94],"pre-processing":[81],"approach,":[82],"exponentiated":[83],"gradient":[84],"adversarial":[86],"debiasing":[87],"in-processing":[89],"approaches,":[90],"threshold":[92],"optimizer":[93],"post-processing":[96],"approach.":[97],"Evaluation":[98],"sensitive":[100],"attributes":[101],"including":[102],"gender,":[103,144],"age,":[104,145],"recording":[105,147],"device's":[106,148],"operating":[107,149],"system,":[108,150],"intersection":[111],"of":[112,156,170,180],"age":[113,159],"gender":[115,157],"revealed":[116],"that":[117],"fairness":[118,182],"could":[119],"be":[120],"substantially":[121],"improved":[122],"with":[123,141],"minimal":[124],"loss":[125],"in":[126],"predictive":[127],"accuracy.":[128],"best":[130],"equalized":[131],"odds":[132],"ratio":[133],"values":[134],"<tex":[136],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[137],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$0.956,0.998$</tex>,":[138],"0.88":[140],"respect":[142],"to":[143],"respectively.":[151],"Similarly,":[152],"combination":[155],"corresponding":[161],"metric":[162],"was":[163],"0.804.":[164],"These":[165],"findings":[166],"support":[167],"feasibility":[169],"fair":[171],"reliable":[173],"audio-based":[174],"systems,":[176],"emphasizing":[177],"importance":[179],"integrating":[181],"into":[183],"pipelines.":[187]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-11T00:00:00"}