{"id":"https://openalex.org/W4226239012","doi":"https://doi.org/10.1109/eebda53927.2022.9744883","title":"Optimization of Deep-Learning Network Using Resnet50 Based Model for Corona Virus Disease (COVID-19) Histopathological Image Classification","display_name":"Optimization of Deep-Learning Network Using Resnet50 Based Model for Corona Virus Disease (COVID-19) Histopathological Image Classification","publication_year":2022,"publication_date":"2022-02-25","ids":{"openalex":"https://openalex.org/W4226239012","doi":"https://doi.org/10.1109/eebda53927.2022.9744883"},"language":"en","primary_location":{"id":"doi:10.1109/eebda53927.2022.9744883","doi":"https://doi.org/10.1109/eebda53927.2022.9744883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eebda53927.2022.9744883","pdf_url":null,"source":{"id":"https://openalex.org/S4363607865","display_name":"IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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":null,"display_name":"Sun Jing","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405279424","display_name":"Zhongshan Polytechnic","ror":"https://ror.org/01es85p39","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279424"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sun Jing","raw_affiliation_strings":["College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400","institution_ids":["https://openalex.org/I4405279424"]}]},{"author_position":"middle","author":{"id":null,"display_name":"He Kun","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405279424","display_name":"Zhongshan Polytechnic","ror":"https://ror.org/01es85p39","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279424"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Kun","raw_affiliation_strings":["College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400","institution_ids":["https://openalex.org/I4405279424"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yao Xin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405279424","display_name":"Zhongshan Polytechnic","ror":"https://ror.org/01es85p39","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279424"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Xin","raw_affiliation_strings":["College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400","institution_ids":["https://openalex.org/I4405279424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005452154","display_name":"Juanli Hu","orcid":"https://orcid.org/0009-0007-2886-3966","observed_orcids":["https://orcid.org/0009-0007-2886-3966"]},"institutions":[{"id":"https://openalex.org/I4405279424","display_name":"Zhongshan Polytechnic","ror":"https://ror.org/01es85p39","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279424"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Juanli","raw_affiliation_strings":["College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhongshan Polytechnic College,Zhongshan,China,528400","institution_ids":["https://openalex.org/I4405279424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405279424"],"apc_list":null,"apc_paid":null,"fwci":1.7478,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.82776801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"992","last_page":"997"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/covid-19","display_name":"COVID-19 pandemic","score":0.9430000185966492},{"id":"https://openalex.org/keywords/chest-ct-images","display_name":"chest CT images","score":0.6200000047683716},{"id":"https://openalex.org/keywords/histopathology-image-classification","display_name":"histopathological image classification","score":0.9470000267028809},{"id":"https://openalex.org/keywords/resnet-50","display_name":"ResNet50","score":0.9150000214576721},{"id":"https://openalex.org/keywords/automated-diagnosis","display_name":"automated diagnosis","score":0.656000018119812},{"id":"https://openalex.org/keywords/medical-image-classification","display_name":"medical image classification","score":0.6299999952316284},{"id":"https://openalex.org/keywords/deep-learning-model-optimization","display_name":"deep learning model optimization","score":0.6940000057220459}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.8444658517837524},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.758538544178009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7454090118408203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6187955141067505},{"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":0.5366548895835876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5088372826576233},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.5043491125106812},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48602229356765747},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4852597415447235},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44141387939453125},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4310379922389984},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4178747534751892},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.406227171421051},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3624914884567261},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.15560728311538696},{"id":"https://openalex.org/C159047783","wikidata":"https://www.wikidata.org/wiki/Q7215","display_name":"Virology","level":1,"score":0.15424814820289612},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.15013307332992554},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14219701290130615},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.1326974332332611},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.10057452321052551},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08894786238670349},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eebda53927.2022.9744883","doi":"https://doi.org/10.1109/eebda53927.2022.9744883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eebda53927.2022.9744883","pdf_url":null,"source":{"id":"https://openalex.org/S4363607865","display_name":"IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9074000120162964,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1974874858","https://openalex.org/W2036109700","https://openalex.org/W2082526668","https://openalex.org/W2294318823","https://openalex.org/W2981903848","https://openalex.org/W3003624604","https://openalex.org/W3010061930","https://openalex.org/W3012135036","https://openalex.org/W3014537881","https://openalex.org/W3016930846","https://openalex.org/W3032017599","https://openalex.org/W3044201655","https://openalex.org/W3048749423","https://openalex.org/W3048886990","https://openalex.org/W3083864010","https://openalex.org/W3086507804","https://openalex.org/W3152711969","https://openalex.org/W4308064182"],"related_works":["https://openalex.org/W4283760398","https://openalex.org/W3049384346","https://openalex.org/W7218364407","https://openalex.org/W4385195272","https://openalex.org/W3139833881","https://openalex.org/W4282017166","https://openalex.org/W4409870592","https://openalex.org/W3209319880","https://openalex.org/W3025508972","https://openalex.org/W3094156029"],"abstract_inverted_index":{"There":[0],"is":[1,101,111,122],"enormous":[2],"attention":[3],"surrounding":[4],"COVID-19":[5,60,108,120],"these":[6],"years.":[7],"Artificial":[8],"Intelligence":[9],"are":[10],"rising":[11],"in":[12,22,156],"the":[13,17,23,46,55,71,90,95,99,104,107,131,137,144,157],"medical":[14,153],"field.":[15],"However,":[16],"next":[18],"revolutionary":[19],"steps":[20],"lie":[21],"upsurge":[24],"of":[25,45,74,89,98,106,134,139],"deep":[26,38],"learning":[27,39,49],"methodology.":[28],"In":[29,142],"this":[30],"study,":[31],"we":[32],"propose":[33],"a":[34],"optimal":[35],"Resnet50":[36],"based":[37],"network":[40],"for":[41,118],"proper":[42],"CT":[43,56,84,116],"diagnosis":[44,73],"COVID-19.":[47],"The":[48,86,115],"model":[50],"was":[51],"then":[52],"adopted":[53],"on":[54],"scan":[57],"images":[58,76],"with":[59],"dataset":[61],"(provided":[62],"by":[63,77],"Zhuhai":[64],"HuiYu":[65],"Medical":[66],"Technology)":[67],"and":[68,79,103,136],"eventually":[69],"achieves":[70],"autonomous":[72],"new":[75],"reading":[78],"analyzing":[80],"more":[81,151],"than":[82],"5000":[83],"pictures.":[85],"preliminary":[87],"results":[88],"core":[91],"system":[92,145],"show":[93],"that":[94],"detecting":[96],"sensitivity":[97],"algorithm":[100],"98.7%,":[102],"accuracy":[105],"case":[109,121],"detection":[110,117],"up":[112],"to":[113,124,149],"97.4%.":[114],"one":[119],"expected":[123],"take":[125],"5.3":[126],"seconds,":[127],"which":[128],"greatly":[129],"reduces":[130],"working":[132],"intensity":[133],"doctors":[135],"number":[138],"misdiagnoses":[140],"significantly.":[141],"addition,":[143],"can":[146],"be":[147],"extended":[148],"other":[150],"extensive":[152],"image":[154],"perception":[155],"future.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-05-05T00:00:00"}