{"id":"https://openalex.org/W3127815853","doi":"https://doi.org/10.1109/bibm49941.2020.9313208","title":"Multimodal Lung Disease Classification using Deep Convolutional Neural Network","display_name":"Multimodal Lung Disease Classification using Deep Convolutional Neural Network","publication_year":2020,"publication_date":"2020-12-16","ids":{"openalex":"https://openalex.org/W3127815853","doi":"https://doi.org/10.1109/bibm49941.2020.9313208","mag":"3127815853"},"language":"en","primary_location":{"id":"doi:10.1109/bibm49941.2020.9313208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313208","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5061472388","display_name":"Zeenat Tariq","orcid":"https://orcid.org/0000-0002-7129-4267"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zeenat Tariq","raw_affiliation_strings":["School of Computing and Engineering, University of Missouri-Kansas City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Engineering, University of Missouri-Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055020287","display_name":"Sayed Khushal Shah","orcid":"https://orcid.org/0000-0002-9309-5656"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sayed Khushal Shah","raw_affiliation_strings":["School of Computing and Engineering, University of Missouri-Kansas City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Engineering, University of Missouri-Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007672179","display_name":"Yugyung Lee","orcid":"https://orcid.org/0000-0002-1619-1695"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yugyung Lee","raw_affiliation_strings":["School of Computing and Engineering, University of Missouri-Kansas City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Engineering, University of Missouri-Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75421653"],"apc_list":null,"apc_paid":null,"fwci":5.704,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.95854922,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2530","last_page":"2537"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9998999834060669,"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/T11309","display_name":"Music and Audio Processing","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12418","display_name":"Respiratory and Cough-Related Research","score":0.9886000156402588,"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/spectrogram","display_name":"Spectrogram","score":0.746493935585022},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7301613092422485},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7270551323890686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.615910530090332},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5886619091033936},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5362939238548279},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5318405628204346},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.47760626673698425},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.46325597167015076},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45714783668518066},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.44992056488990784},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43131494522094727},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4153364896774292},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18852418661117554}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.746493935585022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7301613092422485},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7270551323890686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.615910530090332},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5886619091033936},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5362939238548279},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5318405628204346},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47760626673698425},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.46325597167015076},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45714783668518066},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.44992056488990784},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43131494522094727},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4153364896774292},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18852418661117554},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm49941.2020.9313208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313208","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1533318183","https://openalex.org/W1836465849","https://openalex.org/W1972567154","https://openalex.org/W2038484192","https://openalex.org/W2043392634","https://openalex.org/W2170748564","https://openalex.org/W2188563164","https://openalex.org/W2191779130","https://openalex.org/W2327109843","https://openalex.org/W2534194776","https://openalex.org/W2555677886","https://openalex.org/W2578354350","https://openalex.org/W2702116941","https://openalex.org/W2752143737","https://openalex.org/W2770896033","https://openalex.org/W2806806521","https://openalex.org/W2809598685","https://openalex.org/W2886093827","https://openalex.org/W2898718474","https://openalex.org/W2904556803","https://openalex.org/W2921177942","https://openalex.org/W2930765714","https://openalex.org/W2949117887","https://openalex.org/W3004806247","https://openalex.org/W3007944646","https://openalex.org/W3008569730","https://openalex.org/W3020747538","https://openalex.org/W4230320068","https://openalex.org/W6638667902","https://openalex.org/W6754058454"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W3179495260","https://openalex.org/W1976719989","https://openalex.org/W3127543252","https://openalex.org/W2065606036","https://openalex.org/W2131169870","https://openalex.org/W3014136459"],"abstract_inverted_index":{"Lung":[0,76],"disease":[1,22,36],"is":[2,209],"the":[3,13,21,28,45,52,62,89,94,123,128,138,158,164,188,197,206],"most":[4],"common":[5],"cause":[6],"of":[7,20,24,55,64,191],"severe":[8],"illness":[9],"and":[10,18,114,126,169,174,178,199,212],"death":[11],"in":[12,27,93,131],"World.":[14],"The":[15,31,97,117],"early":[16],"diagnosis":[17],"treatment":[19],"are":[23,38],"great":[25],"importance":[26],"medical":[29,95],"field.":[30,96],"computer-assisted":[32],"systems":[33],"for":[34,176,187],"lung":[35,56,65,167,192],"recognition":[37,54],"effective":[39],"methods":[40],"to":[41,87,151],"help":[42],"physicians":[43],"diagnose":[44],"diseases":[46,66],"effectively.":[47],"Therefore,":[48],"this":[49],"paper":[50],"studies":[51],"multimodal":[53],"sound":[57,133,168],"using":[58,109],"spectrograms.":[59],"Based":[60],"on":[61],"classification":[63,90,190],"by":[67,121],"deep":[68],"convolutional":[69],"neural":[70],"networks,":[71],"an":[72,184],"integrated":[73,185],"network":[74],"Multimodal":[75],"Disease":[77],"Classification":[78],"(MLDC)":[79],"model":[80,186],"was":[81,142],"used":[82,170],"with":[83],"advanced":[84,147],"pre-processing":[85,108],"techniques":[86,111,150],"assess":[88],"accuracy":[91],"acceptable":[92],"research":[98],"has":[99],"three":[100],"main":[101],"contributions.":[102],"First,":[103],"we":[104,145,161,182,204],"have":[105,162,195],"performed":[106],"data":[107,118,141,148,155],"two":[110],"Data":[112,115],"Normalization":[113],"Augmentation.":[116],"were":[119],"normalized":[120],"removing":[122],"unwanted":[124],"noise":[125],"adjusting":[127],"peak":[129],"values":[130],"a":[132],"signal.":[134],"For":[135],"training":[136],"purposes,":[137],"publicly":[139],"available":[140],"insufficient.":[143],"Hence":[144],"applied":[146],"augmentation":[149],"generate":[152],"some":[153],"additional":[154],"without":[156],"affecting":[157],"categories.":[159],"Secondly,":[160],"extracted":[163],"spectrograms":[165],"from":[166],"them":[171],"as":[172],"features":[173],"images":[175],"signal":[177],"image":[179],"processing.":[180],"Finally,":[181],"created":[183],"high-performance":[189],"diseases.":[193],"We":[194],"compared":[196],"audio":[198],"spectrogram":[200],"image-based":[201,207],"results":[202],"where":[203],"found":[205],"approach":[208],"cost-effective,":[210],"efficient,":[211],"reliable.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
