{"id":"https://openalex.org/W4229019129","doi":"https://doi.org/10.1142/s1793557122502400","title":"Transfer learning with NASNet-Mobile for Pneumonia X-ray classification","display_name":"Transfer learning with NASNet-Mobile for Pneumonia X-ray classification","publication_year":2022,"publication_date":"2022-05-04","ids":{"openalex":"https://openalex.org/W4229019129","doi":"https://doi.org/10.1142/s1793557122502400"},"language":"en","primary_location":{"id":"doi:10.1142/s1793557122502400","doi":"https://doi.org/10.1142/s1793557122502400","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793557122502400","pdf_url":null,"source":{"id":"https://openalex.org/S17334899","display_name":"Asian-European Journal of Mathematics","issn_l":"1793-7183","issn":["1793-7183","1793-5571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Asian-European Journal of Mathematics","raw_type":"journal-article"},"volume":null,"type":"article","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":"https://openalex.org/A5006250449","display_name":"Irina Naskinova","orcid":"https://orcid.org/0009-0009-7794-4265","observed_orcids":["https://orcid.org/0009-0009-7794-4265"]},"institutions":[{"id":"https://openalex.org/I168129107","display_name":"South-West University \"Neofit Rilski\"","ror":"https://ror.org/002wcjr61","country_code":"BG","type":"education","lineage":["https://openalex.org/I168129107"]}],"countries":["BG"],"is_corresponding":true,"raw_author_name":"Irina Naskinova","raw_affiliation_strings":["Faculty of Mathematics and Natural Sciences, South-West University \u201cNeofit Rilski\u201d, 66 \u201cIvan Mihaylov\u201d Street, Blagoevgrad 2700, Bulgaria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Natural Sciences, South-West University \u201cNeofit Rilski\u201d, 66 \u201cIvan Mihaylov\u201d Street, Blagoevgrad 2700, Bulgaria","institution_ids":["https://openalex.org/I168129107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006250449"],"corresponding_institution_ids":["https://openalex.org/I168129107"],"apc_list":null,"apc_paid":null,"fwci":1.9423,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.85182351,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"16","issue":"01","first_page":null,"last_page":null},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.0,"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/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/pneumonia-detection","display_name":"pneumonia detection","score":0.9319999814033508},{"id":"https://openalex.org/keywords/chest-x-ray-classification","display_name":"chest X-ray classification","score":0.9800000190734863},{"id":"https://openalex.org/keywords/nasnetmobile","display_name":"NASNetMobile","score":0.871999979019165},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":1.0},{"id":"https://openalex.org/keywords/fine-tuning","display_name":"fine-tuning","score":0.8230000138282776},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9309999942779541},{"id":"https://openalex.org/keywords/computer-aided-diagnosis","display_name":"computer-aided diagnosis","score":0.9909999966621399}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.81232750415802},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7196963429450989},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.6663343906402588},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6046013832092285},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5995734930038452},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46427223086357117},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4566288888454437},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.44267815351486206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4272487759590149},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.27108508348464966},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.07626742124557495},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1793557122502400","doi":"https://doi.org/10.1142/s1793557122502400","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793557122502400","pdf_url":null,"source":{"id":"https://openalex.org/S17334899","display_name":"Asian-European Journal of Mathematics","issn_l":"1793-7183","issn":["1793-7183","1793-5571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Asian-European Journal of Mathematics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.9391000270843506,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1964351375","https://openalex.org/W1997799089","https://openalex.org/W2007058645","https://openalex.org/W2103637444","https://openalex.org/W2117539524","https://openalex.org/W2129245598","https://openalex.org/W2152772232","https://openalex.org/W2183341477","https://openalex.org/W2522861252","https://openalex.org/W2581082771","https://openalex.org/W2608231518","https://openalex.org/W2611650229","https://openalex.org/W2624552887","https://openalex.org/W2772246530","https://openalex.org/W2788633781","https://openalex.org/W2894319790","https://openalex.org/W2897228760","https://openalex.org/W2901158775","https://openalex.org/W2901782819","https://openalex.org/W2914019150","https://openalex.org/W2919115771","https://openalex.org/W3013601031","https://openalex.org/W3014521130","https://openalex.org/W3014834631","https://openalex.org/W3014890122","https://openalex.org/W3016194608","https://openalex.org/W3016488464","https://openalex.org/W3017141460","https://openalex.org/W3025404316","https://openalex.org/W3032155710","https://openalex.org/W3036638392","https://openalex.org/W3113444169","https://openalex.org/W3120967110","https://openalex.org/W4205623122"],"related_works":["https://openalex.org/W4405756109","https://openalex.org/W3188325079","https://openalex.org/W3018007233","https://openalex.org/W3082076807","https://openalex.org/W4306670565","https://openalex.org/W4387940037","https://openalex.org/W3210270038","https://openalex.org/W3017309755","https://openalex.org/W3207161662","https://openalex.org/W3199380665"],"abstract_inverted_index":{"Pneumonia":[0],"affects":[1],"7%":[2],"of":[3,55,131],"the":[4,24,39,125,137,145,186],"population":[5],"worldwide":[6],"and":[7,28,90,94,112,135,174,178],"results":[8,159],"in":[9,72,78,88,195],"about":[10],"four":[11],"million":[12],"deaths":[13],"worldwide.":[14],"The":[15,35,141],"mortality":[16],"caused":[17],"by":[18],"pneumonia":[19,95,193],"can":[20,60,152,171,179],"be":[21,61,82,172,180],"prevented,":[22],"as":[23,75,162],"treatment":[25],"is":[26,38,50,70,77],"low-tech":[27],"low-cost,":[29],"yet":[30],"it":[31,49],"often":[32,48],"goes":[33],"unrecognized.":[34],"chest":[36,196],"X-ray":[37],"most":[40],"reliable":[41],"diagnostic":[42,67,189],"imaging":[43],"technique":[44],"for":[45,53,133,184,192],"pneumonia.":[46],"Yet,":[47],"not":[51],"used":[52],"lack":[54],"trained":[56],"diagnosticians.":[57],"However,":[58],"this":[59,73],"overcome":[62],"with":[63,128,139,148],"deep":[64],"learning":[65,107,122,151,165],"computer-aided":[66,188],"technology,":[68],"which":[69],"shown":[71],"study":[74,100],"well":[76],"previous":[79],"research":[80],"to":[81,84,144,176],"able":[83],"achieve":[85],"high":[86],"performance":[87,127],"detecting":[89],"classifying":[91],"between":[92,104],"healthy":[93],"radio":[96,197],"graph":[97],"images.":[98],"This":[99],"presents":[101],"a":[102,105,113,181],"comparison":[103],"transfer":[106,150,164],"model":[108,126],"based":[109,167],"on":[110,168],"NASNet-Mobile":[111],"custom":[114,115,155],"convolutional":[116],"neural":[117],"network":[118],"(CNN)":[119],"topology.":[120],"Transfer":[121],"has":[123],"enhanced":[124],"an":[129],"average":[130],"5%":[132],"accuracy":[134],"lowered":[136],"loss":[138],"15%.":[140],"experiments":[142],"point":[143],"fact":[146],"that":[147],"fine-tuning,":[149],"greatly":[153],"improve":[154],"CNN":[156],"models.":[157],"These":[158],"are":[160],"significant":[161],"building":[163],"models":[166,170],"simpler":[169],"faster":[173],"cheaper":[175],"industrialize":[177],"viable":[182],"option":[183],"providing":[185],"needed":[187],"support":[190],"system":[191],"detection":[194],"graphs.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2022-05-08T00:00:00"}
