{"id":"https://openalex.org/W4378804472","doi":"https://doi.org/10.1145/3592686.3592749","title":"An improved X-ray image diagnosis method for COVID-19 pneumonia on a lightweight neural network embedded device","display_name":"An improved X-ray image diagnosis method for COVID-19 pneumonia on a lightweight neural network embedded device","publication_year":2023,"publication_date":"2023-02-10","ids":{"openalex":"https://openalex.org/W4378804472","doi":"https://doi.org/10.1145/3592686.3592749"},"language":"en","primary_location":{"id":"doi:10.1145/3592686.3592749","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3592686.3592749","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 3rd International Conference on Bioinformatics and Intelligent Computing","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/A5103253927","display_name":"Ziyang Zhang","orcid":"https://orcid.org/0009-0005-6233-8925"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyang Zhang","raw_affiliation_strings":["College of Computer Science and Cyber Security, Chengdu University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0005-6233-8925","affiliations":[{"raw_affiliation_string":"College of Computer Science and Cyber Security, Chengdu University of Technology, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102962952","display_name":"Yingjie Ma","orcid":"https://orcid.org/0009-0006-5294-7775"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Ma","raw_affiliation_strings":["College of Computer Science and Cyber Security, Chengdu University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0006-5294-7775","affiliations":[{"raw_affiliation_string":"College of Computer Science and Cyber Security, Chengdu University of Technology, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101435804","display_name":"Keran Li","orcid":"https://orcid.org/0000-0002-7296-8729"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keran Li","raw_affiliation_strings":["college of energe, Chengdu University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-7296-8729","affiliations":[{"raw_affiliation_string":"college of energe, Chengdu University of Technology, China","institution_ids":["https://openalex.org/I31595395"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103253927"],"corresponding_institution_ids":["https://openalex.org/I31595395"],"apc_list":null,"apc_paid":null,"fwci":0.671,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7052964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"351","last_page":"357"},"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":0.9800000190734863,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9726999998092651,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7873521447181702},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.6063812375068665},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5860370397567749},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5342492461204529},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.47892555594444275},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.45913559198379517},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.4509734809398651},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4112805724143982},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39166495203971863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3643571734428406},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.33309125900268555},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2936265468597412},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10320651531219482},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10080015659332275}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7873521447181702},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.6063812375068665},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5860370397567749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5342492461204529},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.47892555594444275},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.45913559198379517},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4509734809398651},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4112805724143982},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39166495203971863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3643571734428406},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.33309125900268555},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2936265468597412},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10320651531219482},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10080015659332275},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3592686.3592749","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3592686.3592749","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 3rd International Conference on Bioinformatics and Intelligent Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2044097773","https://openalex.org/W2982083293","https://openalex.org/W3014725478","https://openalex.org/W3015292413","https://openalex.org/W3104810384","https://openalex.org/W3158135439","https://openalex.org/W3177052299","https://openalex.org/W4210637579"],"related_works":["https://openalex.org/W96612179","https://openalex.org/W2770234245","https://openalex.org/W2987774938","https://openalex.org/W2566006169","https://openalex.org/W4256492088","https://openalex.org/W632915154","https://openalex.org/W4229499248","https://openalex.org/W4378874356","https://openalex.org/W2055733372","https://openalex.org/W2369811061"],"abstract_inverted_index":{"With":[0],"the":[1,27,67,79,83,92,97,105,152,158,173,178,214,239,243,257,273,282,291,299,304,307],"continuous":[2],"variation":[3],"and":[4,21,40,59,95,124,138,164,169,200,206,213,245,281,290,301],"evolution":[5],"of":[6,14,82,121,136,216,242,303],"COVID-19,":[7],"Deep":[8],"learning-based":[9],"X-Ray":[10],"image":[11,185],"classification":[12,80,266],"models":[13,39],"COVID-19":[15,181],"have":[16,131],"been":[17,112],"emerged":[18],"a":[19,264],"lot":[20],"achieved":[22],"high":[23,41],"accuracy":[24,81,106,137,292],"rates.":[25],"However,":[26],"current":[28],"mainstream":[29],"neural":[30,68],"network":[31,69,93,155,160],"algorithm":[32],"generally":[33],"has":[34,111,263],"too":[35],"many":[36,188],"parameters,":[37],"complex":[38],"computational":[42,126],"complexity.":[43],"It":[44],"is":[45,53,141,218,234,247],"usually":[46],"deployed":[47,276],"on":[48,74,146,190,227,306],"high-performance":[49],"computing":[50],"servers,":[51],"which":[52,103,221,296],"not":[54,130],"conducive":[55],"to":[56,64,70,109,151,172,236,249,277,287],"embedded":[57,75,148,191,228,279,308],"deployment":[58,226],"real-time":[60],"computing.":[61],"In":[62],"order":[63],"better":[65],"enable":[66],"play":[71],"its":[72,251],"role":[73],"devices":[76],"without":[77],"reducing":[78],"model,":[84],"this":[85,261],"paper":[86,262],"proposes":[87],"MECNet":[88,128,140,258],"(MobileExprCovidNet)":[89],"by":[90],"redesigning":[91],"structure":[94],"transforming":[96],"attention":[98],"mechanism":[99],"with":[100,116,118],"cutting-edge":[101],"knowledge,":[102],"ensures":[104],"rate":[107,293],"compared":[108,150,171],"MobileNetV3":[110,154,176],"greatly":[113],"improved.":[114],"Compared":[115],"networks":[117],"larger":[119],"number":[120,215],"relative":[122],"parameters":[123,217],"higher":[125],"complexity,":[127],"does":[129],"significant":[132],"disadvantages":[133],"in":[134,166,260],"terms":[135],"recall.":[139],"more":[142],"suitable":[143],"for":[144,177,225,268],"implementation":[145],"various":[147],"architecture":[149],"original":[153],"structure.":[156],"Experimentally,":[157],"proposed":[159,259],"improves":[161],"4%":[162],",5%,":[163],"5%":[165],"accuracy,":[167,198],"precision,":[168,199],"recall":[170,201],"base":[174],"model":[175,274,305],"publicly":[179],"accessible":[180],"Radiography":[182],"Database":[183],"dataset":[184,233],"class.":[186],"Outperformed":[187],"metrics":[189],"device":[192],"experiments":[193,254],"GhostNet,":[194],"ResNet50,":[195],"MobileNetV3.":[196],"The":[197,230,253],"rates":[202],"are":[203,211],"92%,":[204],"90%,":[205],"91%,":[207],"while":[208],"only":[209,219],"73MFLOPs":[210],"required,":[212],"0.85M,":[220],"meets":[222],"our":[223],"requirement":[224],"machines.":[229],"Chest":[231],"X-ray":[232],"used":[235,248],"further":[237],"verify":[238,250],"generalization":[240],"ability":[241],"network,":[244],"Score-CAM":[246],"effectiveness.":[252],"demonstrate":[255],"that":[256],"good":[265],"effect":[267],"COVID":[269],"pneumonia":[270],"X-rays.":[271],"Finally,":[272],"was":[275,285],"an":[278],"device,":[280],"processing":[283],"speed":[284],"measured":[286],"reach":[288],"183.3ms,":[289],"reached":[294],"89.7%,":[295],"directly":[297],"proves":[298],"usability":[300],"efficiency":[302],"device.":[309]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}