{"id":"https://openalex.org/W3214848788","doi":"https://doi.org/10.1109/wimob52687.2021.9606355","title":"Multimodal Detection of COVID-19 Symptoms using Deep Learning &amp; Probability-based Weighting of Modes","display_name":"Multimodal Detection of COVID-19 Symptoms using Deep Learning &amp; Probability-based Weighting of Modes","publication_year":2021,"publication_date":"2021-10-11","ids":{"openalex":"https://openalex.org/W3214848788","doi":"https://doi.org/10.1109/wimob52687.2021.9606355","mag":"3214848788"},"language":"en","primary_location":{"id":"doi:10.1109/wimob52687.2021.9606355","is_oa":true,"landing_page_url":"https://doi.org/10.1109/wimob52687.2021.9606355","pdf_url":"https://ieeexplore.ieee.org/ielx7/9605801/9606245/09606355.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/9605801/9606245/09606355.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051923406","display_name":"Meysam Effati","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meysam Effati","raw_affiliation_strings":["Autonomous Systems and Biomechatronics Laboratory (ASBLab)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Systems and Biomechatronics Laboratory (ASBLab)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038315635","display_name":"Yu\u2010Chen Sun","orcid":"https://orcid.org/0000-0001-5994-8961"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210127432","display_name":"SMART Reading","ror":"https://ror.org/0345xq683","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210127432"]}],"countries":["CA","US"],"is_corresponding":false,"raw_author_name":"Yu-Chen Sun","raw_affiliation_strings":["Autonomous Systems and Biomechatronics Laboratory (ASBLab)","Toronto Smart Materials and Structures (TSMART) Department of Mechanical and Industrial Engineering, University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Systems and Biomechatronics Laboratory (ASBLab)","institution_ids":[]},{"raw_affiliation_string":"Toronto Smart Materials and Structures (TSMART) Department of Mechanical and Industrial Engineering, University of Toronto","institution_ids":["https://openalex.org/I185261750","https://openalex.org/I4210127432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003829662","display_name":"Hani E. Naguib","orcid":"https://orcid.org/0000-0003-4822-9990"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I2799838188","display_name":"Toronto Rehabilitation Institute","ror":"https://ror.org/00mxe0976","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I1325899441","https://openalex.org/I2799838188"]},{"id":"https://openalex.org/I4210127432","display_name":"SMART Reading","ror":"https://ror.org/0345xq683","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210127432"]}],"countries":["CA","US"],"is_corresponding":false,"raw_author_name":"Hani E. Naguib","raw_affiliation_strings":["Toronto Rehabilitation Institute","Toronto Smart Materials and Structures (TSMART) Department of Mechanical and Industrial Engineering, University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toronto Rehabilitation Institute","institution_ids":["https://openalex.org/I2799838188"]},{"raw_affiliation_string":"Toronto Smart Materials and Structures (TSMART) Department of Mechanical and Industrial Engineering, University of Toronto","institution_ids":["https://openalex.org/I185261750","https://openalex.org/I4210127432"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061187299","display_name":"Goldie Nejat","orcid":"https://orcid.org/0000-0002-7080-6857"},"institutions":[{"id":"https://openalex.org/I2799838188","display_name":"Toronto Rehabilitation Institute","ror":"https://ror.org/00mxe0976","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I1325899441","https://openalex.org/I2799838188"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Goldie Nejat","raw_affiliation_strings":["Autonomous Systems and Biomechatronics Laboratory (ASBLab)","Toronto Rehabilitation Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Systems and Biomechatronics Laboratory (ASBLab)","institution_ids":[]},{"raw_affiliation_string":"Toronto Rehabilitation Institute","institution_ids":["https://openalex.org/I2799838188"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"151","last_page":"156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9907000064849854,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9790999889373779,"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/weighting","display_name":"Weighting","score":0.8342797160148621},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6805647611618042},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6524620056152344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6162973642349243},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.594092071056366},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5425856709480286},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5342124700546265},{"id":"https://openalex.org/keywords/a-weighting","display_name":"A-weighting","score":0.5309034585952759},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5105592012405396},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.47373974323272705},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.41039302945137024},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3049606680870056},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.10453233122825623},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.10265082120895386}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.8342797160148621},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6805647611618042},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6524620056152344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6162973642349243},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.594092071056366},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5425856709480286},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5342124700546265},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.5309034585952759},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5105592012405396},{"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":0.47373974323272705},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.41039302945137024},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3049606680870056},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10453233122825623},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.10265082120895386},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wimob52687.2021.9606355","is_oa":true,"landing_page_url":"https://doi.org/10.1109/wimob52687.2021.9606355","pdf_url":"https://ieeexplore.ieee.org/ielx7/9605801/9606245/09606355.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/wimob52687.2021.9606355","is_oa":true,"landing_page_url":"https://doi.org/10.1109/wimob52687.2021.9606355","pdf_url":"https://ieeexplore.ieee.org/ielx7/9605801/9606245/09606355.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320312535","display_name":"AGE-WELL","ror":null},{"id":"https://openalex.org/F4320320273","display_name":"University of Cambridge","ror":"https://ror.org/013meh722"},{"id":"https://openalex.org/F4320320994","display_name":"Canada Research Chairs","ror":"https://ror.org/0517h6h17"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3214848788.pdf","grobid_xml":"https://content.openalex.org/works/W3214848788.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W2050613873","https://openalex.org/W2158400027","https://openalex.org/W2221208003","https://openalex.org/W2333826431","https://openalex.org/W2579754298","https://openalex.org/W2776807290","https://openalex.org/W2979780654","https://openalex.org/W3001195213","https://openalex.org/W3008658537","https://openalex.org/W3009231370","https://openalex.org/W3010381061","https://openalex.org/W3011035774","https://openalex.org/W3011040956","https://openalex.org/W3013019084","https://openalex.org/W3013758358","https://openalex.org/W3015034944","https://openalex.org/W3017243633","https://openalex.org/W3023787531","https://openalex.org/W3025798235","https://openalex.org/W3031621189","https://openalex.org/W3035378948","https://openalex.org/W3035825675","https://openalex.org/W3043835827","https://openalex.org/W3047349135","https://openalex.org/W3048804923","https://openalex.org/W3081012644","https://openalex.org/W3088067841","https://openalex.org/W3089349608","https://openalex.org/W3090128366","https://openalex.org/W3092136311","https://openalex.org/W3098200707","https://openalex.org/W3101180623","https://openalex.org/W3105837102","https://openalex.org/W3109783949","https://openalex.org/W3118723804","https://openalex.org/W3122794187","https://openalex.org/W3125483822","https://openalex.org/W3127462145","https://openalex.org/W3142312189","https://openalex.org/W3152531055","https://openalex.org/W3152817622","https://openalex.org/W3158202104","https://openalex.org/W3158767600","https://openalex.org/W3159357214","https://openalex.org/W4323653237","https://openalex.org/W6793053380","https://openalex.org/W6796658603"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W2092002118","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W1880952682","https://openalex.org/W1963516324","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049"],"abstract_inverted_index":{"The":[0,179,201],"COVID-19":[1,105,155,209],"pandemic":[2],"is":[3],"one":[4],"of":[5,30,37,43,58,101,116,119,176,194,199,208],"the":[6,12,19,28,35,40,44,47,56,93,99,120,128,174,190],"most":[7],"challenging":[8],"healthcare":[9],"crises":[10],"during":[11],"21":[13],"<sup":[14],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[15],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">st</sup>":[16],"century.":[17],"As":[18,69],"virus":[20,60],"continues":[21],"to":[22,91,95,153,189,216],"spread":[23,100],"on":[24,34,125,183],"a":[25,53,66,150],"global":[26],"scale,":[27],"majority":[29],"efforts":[31],"have":[32,92],"been":[33,135],"development":[36],"vaccines":[38],"and":[39,62,73,86,97,114,166,197],"mass":[41],"immunization":[42],"public.":[45],"While":[46],"daily":[48],"case":[49],"numbers":[50],"were":[51,181],"following":[52],"decreasing":[54],"trend,":[55],"emergent":[57],"new":[59],"mutations":[61],"variants":[63],"still":[64,89],"pose":[65],"significant":[67],"threat.":[68],"economies":[70],"start":[71,75],"recovering":[72],"societies":[74],"opening":[76],"up":[77],"with":[78,104,187],"people":[79],"going":[80],"back":[81],"into":[82],"office":[83],"buildings,":[84],"schools,":[85],"malls,":[87],"we":[88,148],"need":[90],"ability":[94],"detect":[96],"minimize":[98],"COVID-19.":[102],"Individuals":[103],"may":[106],"show":[107,203],"multiple":[108],"symptoms":[109,126,139],"such":[110],"as":[111],"cough,":[112],"fever,":[113,196],"shortness":[115,198],"breath.":[117,200],"Many":[118],"existing":[121,158,185],"detection":[122,207],"techniques":[123],"focus":[124],"having":[127],"same":[129],"equal":[130,218],"importance.":[131],"However,":[132],"it":[133],"has":[134],"shown":[136],"that":[137,172],"some":[138],"are":[140],"more":[141],"prevalent":[142],"than":[143],"others.":[144],"In":[145],"this":[146],"paper,":[147],"present":[149],"multimodal":[151],"method":[152],"predict":[154],"by":[156],"incorporating":[157],"deep":[159],"learning":[160],"classifiers":[161],"using":[162,210],"convolutional":[163],"neural":[164],"networks":[165],"our":[167,211],"novel":[168],"probability-based":[169],"weighting":[170,212,219],"function":[171,213],"considers":[173],"prevalence":[175],"each":[177],"symptom.":[178],"experiments":[180],"performed":[182],"an":[184,217],"dataset":[186],"respect":[188],"three":[191],"considered":[192],"modes":[193],"coughs,":[195],"results":[202],"considerable":[204],"improvements":[205],"in":[206],"when":[214],"compared":[215],"function.":[220]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}