{"id":"https://openalex.org/W3208849834","doi":"https://doi.org/10.1109/icccnt51525.2021.9579878","title":"Visualization of COVID Bimodal scan using DNN","display_name":"Visualization of COVID Bimodal scan using DNN","publication_year":2021,"publication_date":"2021-07-06","ids":{"openalex":"https://openalex.org/W3208849834","doi":"https://doi.org/10.1109/icccnt51525.2021.9579878","mag":"3208849834"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt51525.2021.9579878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt51525.2021.9579878","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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/A5020260061","display_name":"Amrita Tripathi","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Amrita Tripathi","raw_affiliation_strings":["Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India"],"affiliations":[{"raw_affiliation_string":"Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040397016","display_name":"Abhinandan Basavapattana","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abhinandan Basavapattana","raw_affiliation_strings":["Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India"],"affiliations":[{"raw_affiliation_string":"Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045778191","display_name":"Rekha R Nair","orcid":"https://orcid.org/0000-0002-7207-2877"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rekha R. Nair","raw_affiliation_strings":["Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India"],"affiliations":[{"raw_affiliation_string":"Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022739741","display_name":"Tripty Singh","orcid":"https://orcid.org/0000-0002-3688-4392"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tripty Singh","raw_affiliation_strings":["Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India"],"affiliations":[{"raw_affiliation_string":"Amrita School of Engineering, Bengaluru Amrita Vishwa Vidyapeetham, India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020260061"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":1.2371,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.79559022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"07"},"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":0.9882000088691711,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9801999926567078,"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/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.7663540840148926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6976905465126038},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6246109008789062},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6149690747261047},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5578387379646301},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.5395516753196716},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5291619300842285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4298909306526184},{"id":"https://openalex.org/keywords/viral-pneumonia","display_name":"Viral pneumonia","score":0.4284452199935913},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4181016683578491},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.4160372018814087},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.40378081798553467},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35901010036468506},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2699568271636963},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.24122834205627441},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.2192331850528717},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.2139998972415924},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.12271526455879211}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.7663540840148926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6976905465126038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6246109008789062},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6149690747261047},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5578387379646301},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.5395516753196716},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5291619300842285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4298909306526184},{"id":"https://openalex.org/C2778158872","wikidata":"https://www.wikidata.org/wiki/Q2603200","display_name":"Viral pneumonia","level":5,"score":0.4284452199935913},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4181016683578491},{"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":0.4160372018814087},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.40378081798553467},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35901010036468506},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2699568271636963},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.24122834205627441},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.2192331850528717},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.2139998972415924},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.12271526455879211}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt51525.2021.9579878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt51525.2021.9579878","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2548377017","https://openalex.org/W2745303193","https://openalex.org/W2792643794","https://openalex.org/W2889371659","https://openalex.org/W2899391809","https://openalex.org/W2936534246","https://openalex.org/W2947047703","https://openalex.org/W2972200017","https://openalex.org/W2972440200","https://openalex.org/W3017855299","https://openalex.org/W3035035250","https://openalex.org/W3043662730","https://openalex.org/W3043896182","https://openalex.org/W3048123412","https://openalex.org/W3081802893","https://openalex.org/W3087636224","https://openalex.org/W3089349608","https://openalex.org/W3091548849","https://openalex.org/W3128557465","https://openalex.org/W3139487216","https://openalex.org/W3147750491","https://openalex.org/W4249877648","https://openalex.org/W6779681028","https://openalex.org/W6780516658"],"related_works":["https://openalex.org/W3105985586","https://openalex.org/W2411902499","https://openalex.org/W4297152064","https://openalex.org/W2372777018","https://openalex.org/W2926242485","https://openalex.org/W1517995129","https://openalex.org/W2560654089","https://openalex.org/W3192668266","https://openalex.org/W3025471795","https://openalex.org/W3107765446"],"abstract_inverted_index":{"COVID-19":[0,36,81,161,172,181],"is":[1,22,90,104,194],"a":[2,10,15,178,209],"disease":[3,69],"caused":[4],"by":[5],"SARS-CoV-2":[6],"that":[7,52],"can":[8,26,53,76,158],"arouse":[9],"respiratory":[11],"tract":[12],"infection.":[13],"Therefore,":[14],"rapid":[16],"identification":[17],"of":[18,34,59,80,135,171,192,212,218],"clearly":[19,197],"visualized":[20],"infections":[21],"urgently":[23],"needed,":[24],"which":[25],"assist":[27],"early":[28,78,121],"diagnosis":[29],"and":[30,49,55,73,126,183,216,220],"save":[31],"the":[32,57,84,151,169,190],"lives":[33],"suspected":[35],"patients.Recent":[37],"technological":[38],"progress":[39],"has":[40,207],"made":[41],"it":[42,94],"possible":[43],"to":[44,196],"fuse":[45],"deep":[46,155,204],"learning":[47,156,205],"classification":[48],"medical":[50],"images":[51,125,149],"accelerate":[54],"improve":[56],"accuracy":[58,75,211],"results":[60],"when":[61],"leveraged.":[62],"This":[63,108,154],"could":[64],"particularly":[65],"be":[66],"important":[67],"for":[68,116,168],"where":[70],"faster":[71],"result":[72],"increased":[74],"help":[77],"detection":[79,170],"cases":[82,162],"vis-\u00e0-vis":[83],"traditional":[85],"RT-PCR":[86,166],"tests.":[87],"DNN":[88],"classifier":[89],"designed":[91],"such":[92],"that,":[93],"automatically":[95],"detects":[96],"virus":[97],"present":[98],"in":[99,150],"lungs":[100],"using":[101,122],"chest":[102,123,143,152],"image":[103,199],"termed":[105],"as":[106,120],"Bimodal.":[107],"research":[109],"article":[110],"proposes":[111],"an":[112],"automatic":[113],"frame":[114],"work":[115],"identifying":[117],"COVID":[118,141],"-19":[119],"X-ray":[124,142],"CT":[127],"Scan":[128],"Images.":[129],"For":[130],"this":[131],"experiment,":[132],"3":[133],"types":[134],"data":[136],"set":[137],"are":[138],"used,":[139],"1)":[140],"2)":[144],"CT-scan":[145],"SARS-COV-2,":[146],"3),":[147],"X-Ray":[148],"(Pneumonia).":[153],"model":[157,176,206],"detect":[159],"positive":[160],"more":[163],"quickly":[164],"than":[165],"tests":[167],"cases.":[173],"The":[174,202],"proposed":[175,203],"provides":[177],"relationship":[179],"between":[180],"patients":[182],"pneumonia":[184],"patients.":[185],"Color":[186],"visualization":[187],"approach":[188],"on":[189],"basis":[191],"Grad-CAM":[193],"used":[195],"interpret":[198],"radiology":[200],"detection.":[201],"achieved":[208],"total":[210],"92.33%,":[213],"with":[214],"precision":[215],"recall":[217],"0.94%":[219],"0.93%.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
